{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 图形绘制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 绘制线图\n",
    "* 通过matplotlib.pyplot的plot方法进行图形绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ldPbouF9SWV0oO8SGHRtYs22Nl/dvTbp07OI7QpP4vJeEiEirtH77en73xu/4\n2ak/Y/KwyUBkIGS8xyzUpiCnAIjcPbF7VvcG1pbWREcYRETibOJLE2mb3pYbT77xi2WJUBYAumV2\nIyczR/MxyFeoMIiIxNHKzSt5oPQBxg0ex8HtD/Ydp1ahHE3gJF+lwiAiEkc3LbyJLh26cG3Btb6j\n1Kkgu4Ala5cQdrVPLCWtkwqDiEiclK4r5a/v/JVbTr+F9hntfcepUygnxLbd23h/0/u+o6SUXXt3\ncc2z17Bq8yrfUZpFhUFEJE7GzhtL7869GTlgpO8o9Tox+0QATeAUY6s2r+LZD55lb3iv7yjNosIg\nIhIH81fP58XVL3LbGbfRJi2xL1Dr1K4TxxxyDG9+ogmcYqnvYX358LoPk2ruhepUGEREAuacY+z8\nsQzMGcgFvS/wHadRdOfKYCTK1TDNocIgIhKwvy//O0vWLuGOYXckzQdGKDvE0vVL2VO1x3cUSRAq\nDCIiAaqsqmT8gvGc0+scTss9zXecRivIKWB31W7e3vC27yiSIFQYREQCNP2t6azcvJLbh97uO0qT\nDOg6gDZpbXRaQr6gwiAiEpCdlTu59aVbufj4i+nftb/vOE3SPqM9/Q7rpysl5AsqDCIiAZn6xlQ+\n2/kZE4dM9B2lWQqyC3Sr6xbatXcXg6cP5uX/vOw7SoupMIiIBGDTzk1Mfm0yV514FT0O7uE7TrOE\nckIs37icHXt2+I6StGavmM1rH79Glw7JdWfK2qgwiIgE4PZXbyfswkw4dYLvKM0Wyg4RdmFK15X6\njpK0ZiybwaDDByXt3AvVqTCIiMTYR1s/4g9v/oHrB13PYR0O8x2n2foe1pf2bdprAqdmWlexjhdW\nvsDl/S/3HSUmEnu6MRGRJHTLP2/hoAMO4n8H/a/vKC3SJq0Ned3ydKVEM3Xp2IWFly+kf5fkGvBa\nF+9HGMzsZjML13gs951LRKQ5lm9czp+W/YmbTr2JzAMyfcdpMc342HxplsapR55KVrss31Fiwnth\niHoH6AJ0jT4G+40jItI8v5z/S47MOpIrT7zSd5SYKMgpYPWW1Wzaucl3FPEsUQrDXufcRufcp9HH\nZt+BRESa6vWPX2fmiplMHDKRtultfceJiVBOCEBHGSRhCsPRZvaJma0ys8fMrLvvQCIiTeGcY+y8\nsfTv0p/C4wt9x4mZngf35OB2B2sCJ0mIQY9vACOBFUA34BbgZTPr55zTxb8ikhSe/eBZXvnoFZ67\n+DnSLFGXz/uJAAAXRklEQVT+Fms5MyOUo3EMkgCFwTk3p9qX75jZm8B/gAuBh+t6XVFREVlZ+w8k\nKSwspLAwdZq9iCSHqnAV4+aP47QjT+PsXmf7jhNzoewQD5U+hHMuae626dPj7zzOKUeeQnZmttcc\nxcXFFBcX77ds69atzd6eOedaminmoqXhRefc+FqeywNKSkpKyMvLi384EZEaHln2CJc/fTlv/OgN\nBh4+0HecmJv53kzOf/x8PvrZR3TP0hnj+lTsriD7d9n85szfJOTA19LSUvLz8wHynXNNmpHL+xGG\nmsysI9ALeMR3FhGRhuzeu5tfLfwV3+nznZQsCxC5UgIiAx9VGOqXeUAma4rW0CYt4T5eW8z7iTYz\nu8vMTjWzI83sJOApoBIobuClIiLe3bfkPj7e9jG3nXGb7yiB6ZbZjZzMHM342EhZ7bLo0LaD7xgx\nlwgV6HDgL8AhwEbgVeAbzjld9CsiCW3b7m3c9sptjBowit6de/uOEygNfBTvhcE5p1GKIpKUfvP6\nb9i+Zzu3nH6L7yiBK8guYPJrkwm7cEpdBSKNp391EZFmWL99Pb9d9FvGFIwh56Ac33ECF8oJsW33\nNt7f9L7vKOKJCoOISDNMfCkym+PYwWN9R4mLE7NPBNAETq2YCoOISBOt3LySB0ofYNzgcRzc/mDf\nceKiU7tOHHPIMRrHUIeJL03kpfKXfMcIlAqDiCQln3PI3LTwJrp06MK1Bdd6y+BDKDukKyVqsbZi\nLbe8dAsrNq3wHSVQKgwikjQqKioYc8MYeuT1oHtBd3rk9WDMDWOoqKiIW4bSdaX89Z2/csvpt9A+\no33c3jcRhLJDLF2/lD1Ve3xHSSiP/fsx2qa35cK+F/qOEijvV0mIiDRGRUUFg4YPoqxXGeERYTDA\nwb2r72XB8AUsmruIzMzMwHOMmz+O3p17M3LAyMDfK9EU5BSwu2o373z6DnndNNMuRI50zVg6gwt6\nX0Cndp18xwmUjjCISFIYP3F8pCz0ipYFAINwzzBlvcqYMGlC4BkWfLiAuavmctsZt6XkTH4NGdB1\nAG3S2ui0RDVhF+b6k67nuoHX+Y4SOBUGEUkKs+fNJtwzXOtz4Z5hZs2bFej7O+e4cd6NDMwZyAW9\nLwj0vRJV+4z29Dusn66UqCY9LZ1RXx+VstOCV6fCICIJzzlHZXrll0cWajJYv3s9UxZN4d1P3w1k\nQOTfl/+dJWuXMHnY5FZ9x8aC7AJdKdFKqTCISMIzMzKqMqCuHuCAPTB2/lj63deP7N9lc+lTl/LI\nskf4ZNsnLX7/yqpKxi8Yz9m9zub03NNbvL1kFsoJ8e7Gd9mxZ4fvKBJnKgwikhTOHXYuaatr/5WV\ntiqNKy64gi03bmHOJXO49IRLeffTd7n86cs5fMrhHHfvcYx5fgyzV8xm2+5tTXpf5xzT35rOys0r\nmTx0cix2JamFskOEXZjSdU26M7KkgNY3akdEktJtN93GguELKHNlkbEM0ask0lal0WdlHyZNm8SB\nGQcyvOdwhvccDsDGHRtZWL6QF1e9yKwVs7jnzXtIt3QGHj6QYT2GcWbPMxmYM5CM9Iz93quiooLx\nE8cze95sdqfvZsOWDRzT/xiO6nCUhz1PLH0P60v7Nu1ZvHYxpxx5iu84Ekfmc/KT5jCzPKCkpKSE\nvDxd1iPSmlRUVDBh0gRmzZtFZVolGeEMRgwbwaQJkxq8pNI5x+otq5m3eh4vrn6RBR8uYMuuLXRs\n25HTjjyNYUcN48yjzqR7u+6cdNZJkSsyqheT1Wn0+aBP3C7fTGSDpw/m8IMO56/f/avvKN6s3LyS\nI7KOoG16W99RmqS0tJT8/HyAfOdckw4TqTCISFJyzrVo8GFVuIq31r/1RYF49aNX2VO1h/avtufz\nLp/D0V99TdrKNEZnj2bqHVNbkDz5Fb1QxKz3Z7FqzCrfUbxwztHvvn4MzBnI9POm+47TJC0pDBrD\nICJJqaVXKqSnpXNi9omMHTyW+ZfNZ8uNW5h7yVwyPsmAXrW/Jh6XbyaDgpwCVm9Zzaadm3xH8cLM\neOJ7T/CLk37hO0pcqTCIiAAHZhzIsKOGkdkhs97LNyvTKr3exyIRhHJCAK368srjDj2OPof28R0j\nrlQYRESiGnP5ZkZVRquehwGg58E9ObjdwZrAqZVRYRARqaahyzdHnDkizokSj5kRygm16iMMrZEK\ng4hINbfddBt9PuhD2sq0L480uMiAxz4r+zBpwiSv+RLFvltdt/bTM62JCoOISDWZmZksmruI0dmj\nyZ2dS84zOeTOzmV09mhdUllNKDvEhh0bWLNtje8oEieauElEpIbMzEym3jGVqUxt8eWbqaogpwCI\nDHzsntXdc5r4WPjhQg7tcCj9DuvnO4oXOsIgIlIPlYXadcvsRk5mTqu51bVzjtHPj+b/Xvk/31G8\nUWEQEZFmaU0DH5esXcLyjcsZOWCk7yjeJERhMLNrzOxDM/vczN4ws5DvTCIiUr+C7AKWrF1C2IV9\nRwncjKUzyMnMYWiPob6jeOO9MJjZRcBvgZuBrwPLgDlm1tlrMBERqVcoJ8S23dt4f9P7vqME7vCD\nDqfoG0Wkp6X7juJNIgx6LALud849AmBmVwHfAkYBd/oMJiIidTsx+0QAFn+ymN6de3tOE6xxp4zz\nHcE7r0cYzCwDyAfm71vmIhf1zgMG+colIiIN69SuE8ccckyrGcfQ2vk+JdEZSAc21Fi+Aega/zgi\nItIU+yZwktTnuzCIiEgSC2WHWLp+KXuq9viOIgHzPYbhM6AK6FJjeRdgfX0vLCoqIisra79lhYWF\nFBYWxjSgiIjUrSCngN1Vu3nn03fI65bnO45UU1xcTHFx8X7Ltm7d2uztme95wM3sDeBfzrnrol8b\n8BHwe+fcXbWsnweUlJSUkJenb04REZ8+r/ycgyYfxD3n3MNVJ17lO05M7anaQ9v0tr5jxFRpaSn5\n+fkA+c650qa8NhFOSfwO+ImZXWZmvYH/BxwIzPCaSkREGtQ+oz39DuuXkre6LnqhiHOLz/UdI2H4\nPiWBc+5v0TkXfk3kVMRS4Czn3Ea/yUREpDEKsgtYtGaR7xgxd17v8/hs52e+YyQM74UBwDk3DZjm\nO4eIiDRdKCfEQ289xI49O+jQtoPvODEzvOdw3xESSiKckhARkSQWyg4RdmFK1zXplLgkGRUGERFp\nkb6H9aV9m/aawCnFqTCIiEiLtElrQ163PE3glOJUGEREpMVC2a3nVtetlQqDiIi0WEFOAau3rGbT\nzk2+o7TI+u3r2fL5Ft8xEpIKg4iItFgoJwSQ9EcZJr40kdCDIXxPapiIVBhERKTFeh7ck4PbHZzU\nEzjt2ruL4neK+d5x3yMy6bBUp8IgIiItZmaEcpJ7HMOsFbPYsmsLIweM9B0lIakwiIhITOy71XWy\nHs5fvWU1px15Gsd2PtZ3lISkwiAiIjERyg6xYccG1mxb4ztKs4wdPJYFly/wHSNhqTCIiEhMFOQU\nAJGBj8l6lCHN9LFYF/0/IyIiMdGRjnR4tQOj/mcU3Qu60yOvB2NuGENFRYXvaBIDCXHzKRERSW4V\nFRUMGj6IHT13wMmw1baCg3tX38uC4QtYNHcRmZmZvmNKC+gIg4iItNj4ieMp61UGRwP7rkg0CPcM\nU9arjAmTJviMJzGgwiAiIi02e95swj3DtT4X7hlm1rxZcU4ksabCICIiLeKcozK98ssjCzUZVKZV\nJuRAyKfKnuJ7T3yPPVV7fEdJeCoMIiLSImZGRlUG1NUHHGRUZSTk7IlmRse2HWmb3tZ3lISnwiAi\nIi127rBzSVtd+0dK2qo0Rpw5Is6JGuf83ufz8HkP+46RFFQYRESkxW676Tb6fNCHtJVpXx5pcJC2\nMo0+K/swacIkr/mk5VQYRESkxTIzM1k0dxGjs0eTOzuXnGdyyJ2dy+js0bqkMkVoHgYREYmJzMxM\npt4xlalMxTmXkGMWpPl0hEFERGJOZSH1qDCIiEirsje8l7Crfc4IqZsKg4iItCpPlT1F7t25/HfX\nf31HSSpeC4OZlZtZuNqjysxu8JlJRERS28NLH+bwgw6nU7tOvqMkFd+DHh0wAXiQL+cI023NREQk\nEGsr1jJn1Rzu+9Z9vqMkHd+FAWC7c26j7xAiIpL6nn3/Wdqmt+XCvhf6jpJ0EmEMw1gz+8zMSs3s\nejNL9x1IRERS00/yf8KK0St0OqIZfB9hmAqUApuBk4DJQFfgep+hREQkdR2RdYTvCEkp5oXBzG4H\nbqxnFQf0cc6975y7u9ryd8xsD3C/mY1zzlXW9z5FRUVkZWXtt6ywsJDCwsLmRhcREUkZxcXFFBcX\n77ds69atzd6exfp2o2Z2CHBIA6utds7treW1xwFvA72dcx/Usf08oKSkpIS8vLwW5xUREWktSktL\nyc/PB8h3zpU25bUxP8LgnNsEbGrmy78OhIFPY5dIREREWsrbGAYz+wYwEFhI5FLKk4DfAY8655p/\nzERERERizudVEruB7wP/BN4BxgG/Ba70mElERFLM2oq1/HL+L9m0s7kHvwU8Fgbn3FvOuUHOua85\n5zo45/o55+5saLCjiIhIU7zz6TvMWDqD9DRdtd8Svi+rFBERCdTwnsP5uOhjFYYWSoSJm0RERAKl\nstByKgwiIiLSIBUGERERaZAKg4iIiDRIhUFEREQapMIgIiIpZ13FOoY+MpT3N73vO0rKUGEQEZGU\n89i/H+P1j1/nsA6H+Y6SMlQYREQkpTjnmLFsBhf0voBO7Tr5jpMyVBhERCSlLFm7hOUblzNywEjf\nUVKKCoOIiKSUE7qcwJMXPsnQHkN9R0kpmhpaRERSygFtDuCCPhf4jpFydIRBREREGqTCICIiIg1S\nYRAREZEGqTCIiIhIg1QYREQk6TnnePydx6nYXeE7SspSYRARkaS3YtMKCv9RyKI1i3xHSVm6rFJE\nRJJe7869+c/P/kN2ZrbvKClLhUFERFJC96zuviOkNJ2SEBERkQapMIiIiEiDVBgSQHFxse8IMZNK\n+wLan0SWSvsC2p9Elkr70hKBFQYz+6WZvWZmO8xscx3rdDezZ6PrrDezO82s1ZWYVPpmTKV9Ae1P\nIkulfQHtT3M45wJ/D0i9f5vmCvLDOQP4G3BfbU9Gi8FzRAZefgO4HBgJ/DrATCIiksQqKioYc8MY\neuT1oHtBdzod14lLrr2EigrNvxC0wK6ScM7dCmBml9exyllAb2CIc+4z4G0zuwmYbGa3OOf2BpVN\nRESST0VFBYOGD6KsVxnhEWEwwEHxqmKWDl/KormLyMzM9B0zZfk8/P8N4O1oWdhnDpAF9PUTSURE\nEtX4ieMjZaFXtCwAGIR7hSnrVcaESRO85kt1Pudh6ApsqLFsQ7XnltXxunYAZWVlAcWKv61bt1Ja\nWuo7Rkyk0r6A9ieRpdK+gPanMf4+6++ETwvD2q8+Fz4wzBOznuDyi+o6qN18qfRvU+2zs12TX+yc\na/QDuB0I1/OoAo6p8ZrLgc21bOt+4Pkay9pHt3NWPRkuBpweeuihhx566NHsx8VN+fx3zjX5CMNv\ngIcbWGd1I7e1HgjVWNal2nN1mQP8ACgHdjXyvURERCRyZCGXyGdpkzSpMDjnNgGbmvomdVgE/NLM\nOlcbxzAc2AosbyDDX2KUQUREpLV5vTkvCmwMg5l1B74GHAmkm1n/6FMrnXM7gLlEisGjZnYj0A2Y\nCPzBOVcZVC4RERFpOgtq4gszexi4rJanhjjnXo6u053IPA2nAzuAGcA451w4kFAiIiLSLIEVBhER\nEUkdrW4aZhEREWk6FQYRERFpUFIVhlS/oZWZHW1mT5vZRjPbamavmNnpvnM1l5l9y8zeMLOdZrbZ\nzJ70namlzKytmS01s7CZneA7T3OY2ZFm9pCZrY7+23xgZreYWYbvbI1lZteY2Ydm9nn0e6zmJdoJ\nz8zGmdmbZrbNzDaY2VNmdozvXLFiZmOjPye/852lucws28weNbPPoj8ry8wsz3eupjKzNDObWO1n\nfqWZNXlazKT4IK0m1W9o9SyQTmQQaB6R2S6fMbPDfIZqDjP7H+AR4I/A8cBJpMblsHcCa4hMfJKs\nehOZWPcnwHFAEXAVcJvPUI1lZhcBvwVuBr5O5Odkjpl19hqs6U4B7gEGAsOI/H6ba2btvaaKgWiB\nu4K6Z+xNeGbWCXgN2E3k3kd9gJ8DW3zmaqaxwJXAT4n8/N8A3GBmo5u0labO9JQID+qePfIcoBLo\nXG3ZlUT+gdv4zt3APh1CZJbLk6st6xhddobvfE3cl3TgY2Ck7ywx3q9zgHejP3Bh4ATfmWK4b9cT\nueTZe5ZGZH0DmFrtayNS4m7wna2F+9U5+n012HeWFu5HR2AFcAawEPid70zN3I/JwEu+c8RoX2YD\nD9ZY9nfgkaZsJ9mOMDQkaW9o5SITUr0HXGZmB5pZG+BqIvfXKPEarunygGwAMys1s7Vm9pyZJfS/\nQX3MrAvwAHAJ8LnnOEHoBNR6mi+RRE+b5APz9y1zkd9+84BBvnLFSCciR64S/t+hAfcCs51zC3wH\naaFzgSVm9rfoKaNSM/ux71DN9Dow1MyOBojOi3QykSPyjZZqhaGhG1olujOJfNhWEPlQug442zm3\n1WuqpjuKyF99NxM5HfQtIkd5/hk9zJeMHgamOefe8h0k1sysFzAa+H++szRCZyJHsGr7OU+Gn/Fa\nmZkBdwOvOufqnOk20ZnZ94EBwDjfWWLgKCJ/tK0gMgvxfcDvzexSr6maZzLwOPCeme0h8kfo3c65\nvzZlI94Lg5ndHh0YU9ejKpkHAjVx/6YR+cV3MpH7bDxNZAxDl7q2H09N2Jd931eTnHNPRz9kf0jk\nr6fveduBGhq7P2Y2hshh1jv2vdRj7Do152fJzHKA54HHnXPT/SQXIj/7xwHf9x2kuczscCKl5wcu\nNWbrTQNKnHM3OeeWOeceBB4kMt4n2VxE5MaN3ycy7udy4BdNLT8+b2+9TyLc0CpIjdo/MxsKfBPo\n5CJTZwOMNrPhRP5x7wwwY2M19t8qO/rfX9xH1Tm3x8xWA0cElK05GrM/HwJDiBzu3h35Q/ALS8zs\nz865HwaUr6ma9LNkZtnAAiJ/1V4ZZLAY+ozIXXFrlugu+PsZbxEz+wORn/1TnHPrfOdpgXzgUKDU\nvvxBSQdOjQ6uOyB6+ihZrKPa77CoMuA7HrK01J3A7c65J6Jfv2tmuUSOBD3a2I14LwwuAW5oFaTG\n7l90ZLQjMuipujAJcCQImrQvJURGFh9L9CYn0XPPucB/AozYJE3Yn2uB8dUWZRMZG3Mh8GYw6Zqu\nKT9L0SMLC4DFwKggc8WSc64y+v01FJgFXxzOHwr83me25oiWhfOA05xzH/nO00LziFwRVd0MIh+y\nk5OsLEDkColjayw7lgT6HdYEBxIp2tU1+bPFe2FoCkvtG1otAv4LPGJmE4mMYbiCyIfssx5zNZlz\nrsLM/h9wq5mtIfIDdgORQvREvS9OQM65NdW/NrMdRE5LrHbOrfWTqvmiRxb+SeToyQ3AYfv+IHTO\n1RwbkIh+B8yIFoc3iVwWeiCRD6ekYWbTgEJgBLCj2qnHrc65Xf6SNU/0d/B+f5hFf1Y2Oedq/qWe\nDKYAr5nZOCKX8w8EfkzkcuRkMxuYEP19/C6RsXJFwENN2orvyz2aeGnIw0RaUs3HqdXW6Q48A2wn\nMh7gDiDNd/ZG7l8ekfPJG4mUh9eA4b5zNXNf0okcBlsX3Zc5QB/fuWK0b0dGv++S8rJKIqe4av4M\nhYEq39masA8/BcqJFOtFwIm+MzVjH8J1/D67zHe2GO7jApL0sspo/m8C/wZ2Rj9oR/nO1Mz96ECk\naH9I5EaPHwC30sTpBnTzKREREWlQQpwbFxERkcSmwiAiIiINUmEQERGRBqkwiIiISINUGERERKRB\nKgwiIiLSIBUGERERaZAKg4iIiDRIhUFEREQapMIgIiIiDVJhEBERkQb9f3eIdxNPwK9VAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xac97d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制一个点，点默认情况下是不显示的，如果需要让点能够显示，需要设置（marker参数可以设置点显示形状）\n",
    "plt.plot(20,marker = 'd')\n",
    "\n",
    "# 绘制多个数据，构成线性形状，如果我们只提供一组数据，则该组数据表示纵坐标，横坐标默认从0 1 2 3 排列\n",
    "plt.plot([3,2,9,15,-3],marker = 'o')\n",
    "\n",
    "# 我们也可以自己来指定横坐标，提供两组数据，第1个列表指定横坐标，第2个列表指定纵坐标\n",
    "#plt.plot([-3, -1, 5, 8, 12], [2, -10, 9, 3, 6],marker = 'o')\n",
    "\n",
    "# 我们在绘制图形的时候，可以指定点的形状，线的形状，线条颜色等设置\n",
    "#plt.plot([-3, -1, 5, 8, 12], [2, -10, 9, 3, 6],'r-.>') # 顺序：线的颜色，线，线的形状，点的形状\n",
    "\n",
    "# 绘制多个数据，每个数据都给予不同的格式\n",
    "#plt.plot([-3,-9],[32,18],'r--D',[5,8],[-10,20],'g-.o')\n",
    "# 以上的方法也可以分两步进行\n",
    "plt.plot([-3,-9],[32,18],'r--D')\n",
    "plt.plot([5,8],[-10,20],'g-.o')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 图形交互式设置\n",
    "* 可以设置jupyter notebook图形是否交互式显示，默认为否\n",
    "* %matplotlib notebook\n",
    "* %matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#% matplotlib notebook\n",
    "plt.plot([5,8],[-10,20],'g-.o')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Mje80+o4BAEAgbkN4dOnvLtXOvTv19BVPMy4BAJCxKAse3Tz9Zh3S/xCKAgAg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\nRRQ2Rd6k3wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xac82b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "% matplotlib inline\n",
    "plt.plot([4,6],[5,8],'g-.o')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 设置中文支持\n",
    "matplotlib默认情况下不支持中文显示，如果需要显示中文，则我们需要做一些额外的设置操作。设置可以分为：\n",
    "* 全局设置\n",
    "* 局部设置\n",
    "\n",
    "### 全局设置\n",
    "我们可以通过执行：  \n",
    "`mpl.rcParams[\"font.family\"] = \"中文字体名称\"`  \n",
    "`mpl.rcParams[\"axes.unicode_minus\"]=False`  \n",
    "进行设置。常用的设置如下:\n",
    "* font.family 字体的名称\n",
    " + sans-serif 西文字体（默认）\n",
    " + SimHei 中文黑体\n",
    " + FangSong 中文仿宋\n",
    " + YouYuan 中文幼圆\n",
    " + STSong 华文宋体\n",
    " + Kaiti 中文楷体\n",
    " + LiSu 中文隶书\n",
    "* font.style 字体的风格\n",
    " + normal 常规（默认）\n",
    " + italic 斜体\n",
    " + oblique 倾斜\n",
    "* font.size 字体的大小（默认10）\n",
    "* axes.unicode_minus 是否使用Unicode的减号（负号）【在支持中文显示状态下，需要设置为False】\n",
    "\n",
    "### 局部设置\n",
    "在需要显式的文字中，使用fontproperties参数进行设置。  \n",
    "\n",
    "说明：\n",
    "* 如果全局设置与局部设置冲突，以局部设置为准。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LrruAJWuW8ODjD/Ke/+4zuZJUhIGBAQYGBvbZtm3btqZfN4r622FEnAasAV6VmT+t4/gV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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xaf7d9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 对字体进行设置，默认的字体不支持中文显示\n",
    "mpl.rcParams['font.family'] = 'SimHei'\n",
    "# 对于西方文字，使用普通的负号来显示，无需设置该选项\n",
    "# 当设置支持中文字体时，会使用unicode的负号来进行显示（不支持），需要将负号显示成普通形式，而不是使用unicode的负号显示\n",
    "mpl.rcParams['axes.unicode_minus'] = False\n",
    "mpl.rcParams['font.style'] = 'normal'\n",
    "mpl.rcParams['font.size'] = 10\n",
    "plt.plot([-3,-2],[-1,-5],'g--')\n",
    "#显示标题\n",
    "plt.title('中文')\n",
    "#局部设置\n",
    "plt.title('中文',fontproperties = 'Kaiti',fontsize = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 保存图表\n",
    "* 通过plt的savefig方法将当前的图形保存到硬盘或者类文件对象中\n",
    "    + dip：每英寸分辨率点数\n",
    "    + facecolor：设置图像的背景色\n",
    "    + bbox_inches：设置为tight，可以紧凑保存图像，即背景空白处较少"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x9478710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# savefig 图表保存\n",
    "# 1、保存到硬盘上\n",
    "plt.plot([1,5,8,10],[2,3,9,6],'r-.o')\n",
    "plt.savefig('C:/Users/oub/Desktop/1.png',dip = 100,facecolor = 'gray',bbox_inches = 'tight')\n",
    "\n",
    "# 2、保存到类文件对象中\n",
    "from io import BytesIO\n",
    "data = BytesIO()\n",
    "plt.savefig(data)\n",
    "#data.read()\n",
    "#data.getvalues()[:100]\n",
    "\n",
    "from PIL import Image\n",
    "# 从硬盘读取文件\n",
    "image = Image.open('C:/Users/oub/Desktop/1.png')\n",
    "image.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 从类文件对象中读取信息\n",
    "image = Image.open(data)\n",
    "image.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 颜色，点标记与线形设置\n",
    "我们可以在绘制图形时，显式指定图形的颜色，点标记或线条形状。\n",
    "    + color（c）：线条颜色\n",
    "    + linestyle（ls）：线条形状\n",
    "    + linewidth（lw）：线宽\n",
    "    + marker：点标记形状\n",
    "    + markersize（ms）：点标记的大小\n",
    "    + markeredgecolor（mec）：点边缘颜色\n",
    "    + markeredgewidth（mew）：点边缘宽度\n",
    "    + markerfacecolor（mfc）：点的颜色\n",
    "说明\n",
    "    + 颜色，点标记与线型可以使用一个参数进行设置\n",
    "    + 颜色除了可以使用预设简写的字符外，也可以使用全称，也可以使用RGB颜色表示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KkaS+bMOGvb9fyK2dGnMR329zvFRMuvToZEQcDZwJfGgfu74AHN5q2+HAtpTSzn0dZ+7c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\nIcOCJEnqkGFBkiR1yLAgSZI69P8BHwqGU/GROmUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xae89080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1,2,3,4],[5,6,7,8],c = 'g',ls = '--',lw = 2,marker = 'o',ms = 10,mew = 2,mec = 'b',mfc = 'r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 透明度设置\n",
    "在绘制图像时，我们可以通过alpha参数来控制图像的透明度，值在0~1之间，0为完全透明，1为不透明"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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29ElSqxj+aqry4C+09GWz8y19SZKU3KVPkrSyDH81VaGit68vWbClz4peSWod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\nxxj+kiT1mP8PNXECykUVvHkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x944e400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.arange(30),marker = 'D',alpha = 0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 图例设置\n",
    "在绘制多条线时，可以设置图例来标注每条线所代表的含义，使图形更加清晰易懂。  \n",
    "可以采用如下的方式设置图例：\n",
    "* 调用plt的legend函数，传递一个标签数组，指定每次plot图形的标签。\n",
    "* 在绘制的时候通过label参数指定图例中显示的名称，然后调用legend函数生成图例。\n",
    "\n",
    "legend常用的参数：\n",
    "* loc：指定图例的位置。默认为best。也可以指定坐标（元组），基于图像左下角计算。\n",
    "* frameon：设置是否含有边框。\n",
    "* title：设置图例的标题。\n",
    "* ncol：图例显示的列数，默认为1。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/O/h8uANBVVW2Fmxtc0dCY1jN28C/W3Bet/O4pJc2znSB4k8MgijHbhaf6mPD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\n6J5MTQJlHJwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xae10320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可以采用两种方式。\n",
    "# plt.legend设置显示图例。\n",
    "\n",
    "# 1 第一种方式，绘图时不指定标签，而在legend方法中指定标签\n",
    "plt.plot(list(range(1,13)),np.random.randint(50,100,12))\n",
    "plt.plot(list(range(1,13)),np.random.randint(50,100,12))\n",
    "\n",
    "# loc 控制图例的显示位置，默认为best，即选择一个最好的位置\n",
    "#plt.legend(['2016','2017'],loc = 'upper left')\n",
    "\n",
    "# legend也可以指定图例的坐标。（坐标的值基于当前图形的比例。）\n",
    "#plt.legend([\"2016\", \"2017\"], loc=(0.6, 0.8))\n",
    "\n",
    "# frameon是否显示图例的边框，True（默认值）显示，False不显示。\n",
    "#plt.legend(['2016','2017'],frameon = False)\n",
    "\n",
    "# ncol一行显示几个标签\n",
    "plt.legend([\"2016\", \"2017\",'2018'], loc=\"lower right\", title=\"年降雨量\", ncol = 2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8sH69zJRX7ti6Vf4/SKQr/7Q0OO64BLjv//VqeO80uWU67la3o4maJv8k9NBD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\nl5HkL4QQQtxl/h9swBZ0ebHz/AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xaf5a908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2 第2中方式：在绘图时指定标签，在legend中不指定。\n",
    "# 通过label参数指定标签信息。该信息可以用来当做legend的图例标签。\n",
    "plt.plot(list(range(1, 13)), np.random.randint(50, 100, 12), label=\"2016\",c = 'orange')\n",
    "plt.plot(list(range(1, 13)), np.random.randint(50, 100, 12), label=\"2017\")\n",
    "plt.legend(loc=\"lower left\",title = '年降雨量',ncol = 2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 网格设置\n",
    "可以通过plt的grid方法来设置是否显示网格。True为显示，False不显示。ax.grid(color='r', linestyle='-', linewidth=2)\n",
    "* color：设置网格线颜色\n",
    "* axis：设置网格线显示x，y或者全部显示（x，y，both）。\n",
    "* linestyle：设置网格线形状。\n",
    "* linewidth：设置网格线宽度。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fAt4OvGL+PQP3EWk3jT0QEVku7OWGQeAGdz86/7oAXNJgn3XAr7n7JICZ/SXw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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xafda390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1,2],[3,4])\n",
    "plt.grid(True,color = 'y',axis = 'both',ls ='--',lw = 3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 绘图区域设置\n",
    "我们可以在一张图上绘制多个图形，当然，我们也可以将不同的图形绘制到多个不同的区域当中。  \n",
    "我们可以采用以下方式来实现多个区域的绘制（创建子绘图区域）：\n",
    "* 通过Figure对象调用add_subplot方法。\n",
    "* 通过plt的subplot方法。\n",
    "* 通过plt的subplots方法。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 子区域1：add_subplot方法\n",
    "* 首先创建matplotlib.figure.Figure对象，然后通过Figure对象的add_subplot方法增加子绘图区域。  \n",
    "* add_subplot方法中，需要指定子区域的行数、列数与当前要绘制的子区域。  \n",
    "* add_subplot方法会返回子绘图对象（轴对象），通过该对象即可实现绘图（matplotlib.axes._subplots.AxesSubplot）。\n",
    "\n",
    "在绘制图形时，总是需要创建Figure对象。如果没有显式创建，则plt会隐式创建一个Figure对象。在绘制图形时，既可以使用plt来绘制，也可以使用子绘图对象来绘制。  \n",
    "如果使用plt对象绘制，则总是在最后创建的绘图区域上进行绘制，如果此时尚未创建绘图区域，则会自动创建。  \n",
    "\n",
    "\n",
    "说明：\n",
    "* add_subplot方法的参数，即可以使用三个参数分开传递，也可以使用一个参数整体传递。\n",
    "* 可以通过plt.subplots_adjust方法来调整子绘图的位置与子绘图之间的距离。（left, right, top, bottom, wspace, hspace）\n",
    "* 创建子区域时，可以使用facecolor设置绘图区域的背景色。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3vgWIZmuwc+dbWL9+mCuv/J35LE/qJUcDl2fmjZn5JPAF4DXALwJ9OK/1lBUrPsIjj/wm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\nkiQVM1BIkqRi/x8vbpG3jgA6DQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9504e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 创建Figure对象，在我们进行绘图时，一定会存在figure对象\n",
    "figure = plt.figure()\n",
    "\n",
    "# 创建一个子绘图区域，分别指定行数（第1个参数），列数（第2个参数），当前自绘图区域（第3个参数）\n",
    "figure.add_subplot(1, 2, 1)\n",
    "plt.plot(10,marker = 'o')\n",
    "# 三个参数也可以作为一个参数整体传递\n",
    "figure.add_subplot(122)\n",
    "plt.plot(20,marker = 'd')\n",
    "\n",
    "# 调整水平的间距。\n",
    "plt.subplots_adjust(wspace=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RJHh1RUm52bPnM3znOy/kwIF7yy5FfaznmwRTBEk5Wr78Ep73vK+xcOGpZZei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\nkqRx2SRIkqRx/X/XicoCSopPfAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc50e9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 创建Figure对象，在我们进行绘图时，一定会存在figure对象\n",
    "figure = plt.figure()\n",
    "\n",
    "# 在调用add_subplot方法时，会返回所创建的子绘图区域对象，可以通过plt.plot进行绘制\n",
    "sub = figure.add_subplot(121)\n",
    "sub.plot([1,2,3],[4,5,6],'g')\n",
    "sub2 = figure.add_subplot(122)\n",
    "sub2.plot([4,5,6],[1,2,3],'y-.')\n",
    "\n",
    "# 调整水平的间距。\n",
    "plt.subplots_adjust(wspace=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 子区域2：subplot方法\n",
    "通过调用plt的subplot方法创建子绘图区域，该方法返回子绘图对象。此处方式下，会隐式创建Figure对象。  \n",
    "实际上，这种创建子绘图区域的方式，底层也是通过第一种方式实现的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x93dfd68>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0oKJIPzYyayR//uSf/Y4hcaTbEDKgrNm6huN/czwvbHzB7ygi0ksbqjZw+ZLLWbN1jd9R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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xad1cc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制一个2行1列的绘图区域\n",
    "plt.subplot(211)   # 第1行1列第一个绘图区域\n",
    "plt.plot([4,7,5],'g-.d')\n",
    "plt.subplot(2,1,2) # 第2行1列第二个绘图区域\n",
    "plt.plot([1,4,8],'y-o')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 子区域3：subplots方法\n",
    "通过plt的subplots方法创建子绘图区域，该方法返回一个元组（Figure对象与所有子绘图对象，如果是多个子绘图对象，则返回一个ndarray数组）。可以通过sharex与sharey来指定是否共享x轴与y轴"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure(576x576)\n",
      "[[<matplotlib.axes._subplots.AxesSubplot object at 0x000000000C8385C0>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x000000000DC4ADA0>]\n",
      " [<matplotlib.axes._subplots.AxesSubplot object at 0x000000000DDEF5F8>\n",
      "  <matplotlib.axes._subplots.AxesSubplot object at 0x000000000E009B38>]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xdd8b400>]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xIh4fEYfUMJPmlFGpjnk4o2PotRFxZ0RcERE/tsM+jwA+su72xxmd9ZQqY1SqSROHZUTc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\nunOGPgwqlGEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe54bb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 返回元组， 第1个元素，Figure对象，第2个元素：子绘图区域对象。\n",
    "#如果我们创建多个子绘图区域对象，则多个子绘图区域对象会存放在ndarray中。\n",
    "figure,ax = plt.subplots(2,2,sharex = True,sharey = False)\n",
    "figure.set_size_inches(8, 8)  # 设置绘图区域的尺寸大小\n",
    "print(figure)\n",
    "print(ax)\n",
    "ax[0][0].plot([3,9])\n",
    "ax[0][1].plot([4,6])\n",
    "ax[1][0].plot([1,9])\n",
    "ax[1][1].plot([7,2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 绘图区域大小设置\n",
    "如果绘图子区域较多，可能会有些拥挤。此时，我们可以调整绘图区域的大小。方式如下：\n",
    "* 在调用`plt.figure()`创建Figure对象时，通过figsize参数指定。单位为英寸。\n",
    "* 在创建Figure对象后，可以通过Figure对象的set_size_inches方法设置。\n",
    "\n",
    "说明：\n",
    "* 如果没有显式创建Figure对象，可以通过plt的gcf函数获取当前的Figure对象。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xdececc0>]"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xde46550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xdcae5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 在创建figure对象时，通过figsize参数指定绘图区域的大小\n",
    "plt.figure(figsize = (3,3))\n",
    "plt.plot([1,2,4])\n",
    "\n",
    "# 在创建Figure对象后，可以通过Figure对象的set_size_inches方法设置\n",
    "figure = plt.figure()\n",
    "figure.set_size_inches(5,5)\n",
    "plt.plot([4,7,10])\n",
    "\n",
    "# 如果没有显式创建Figure对象，可以通过plt的gcf函数获取当前的Figure对象\n",
    "figure2 = plt.gcf() # 获取当前的figure对象  公用同一个绘图区域\n",
    "#figure2.set_size_inches(5,5)\n",
    "plt.plot([1,2,3])  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 标签与刻度设置\n",
    "可以通过plt对象的相关方法来设置（或获取）标签与刻度等信息。设置还是获取，取决于是否传递实际参数。\n",
    "* plt.xlim 设置或获取x轴刻度范围。\n",
    "* plt.ylim 设置或获取y轴刻度范围。\n",
    "* plt.xticks 设置或获取x轴显示的刻度与标签。\n",
    "* plt.yticks 设置或获取y轴显示的刻度与标签。\n",
    "* plt.axis 可以同时设置或获取x与y轴的刻度范围，或者是取消刻度显示。\n",
    " + 无参数：返回一个元组。(xmin, xmax, ymin, ymax)\n",
    " + (xmin, xmax, ymin, ymax) 同时设置x与y轴的刻度范围。\n",
    " + off 取消坐标轴显示。\n",
    " + tight：坐标轴紧凑显示。\n",
    " + equal：x与y具有同样的长度。\n",
    " \n",
    "## 轴标签说明与标题设置\n",
    "* plt.xlabel 设置x轴的标签说明。\n",
    "* plt.ylabel 设置y轴的标签说明。\n",
    "* plt.title 设置标题。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1.0, 5.0)\n",
      "(2.0, 6.0)\n",
      "(array([  0.,   2.,   4.,   6.,   8.,  10.]), <a list of 6 Text xticklabel objects>)\n",
      "(array([ -2.,   0.,   2.,   4.,   6.,   8.,  10.]), <a list of 7 Text yticklabel objects>)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0xdea2320>,\n",
       "  <matplotlib.axis.XTick at 0xdc12a90>,\n",
       "  <matplotlib.axis.XTick at 0xdf1ff98>],\n",
       " <a list of 3 Text xticklabel objects>)"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bzTk0GV2BvyXJK5Z47VkZBf6KrTkMquqxSY5L8s6JzT+R5N3jyyGLfS/JG8b7fHxi+wOr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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xdf1ff28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1,3,5],[2,4,6])\n",
    "# 显示x轴刻度范围\n",
    "print(plt.xlim())\n",
    "# 显示y轴刻度范围\n",
    "print(plt.ylim())\n",
    "\n",
    "# 除了获取之外，我们也可以去设置x与y轴的刻度范围。\n",
    "plt.xlim(0,10)\n",
    "plt.ylim(-2,10)\n",
    "\n",
    "# 获取x与y的刻度信息。\n",
    "print(plt.xticks())\n",
    "print(plt.yticks())\n",
    "\n",
    "# 设置x与y的刻度信息\n",
    "plt.xticks([0,5,10])\n",
    "plt.yticks([-2,4,10])\n",
    "\n",
    "# 默认情况下，标签就是我们设置的刻度信息。我们可以自定义每个刻度的显示标签\n",
    "plt.xticks([0, 5, 10], [\"偏低\", \"中等\", \"偏高\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xadb5438>]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xadb5128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# axis的使用\n",
    "plt.plot([1,3,5],[2,4,6])\n",
    "\n",
    "# 可以通过axis来设置或者返回x与y轴的界限。\n",
    "# 获取 \n",
    "plt.axis()  # 对应(xmin, xmax, ymin, ymax)\n",
    "\n",
    "# 设置(xmin, xmax, ymin, ymax)\n",
    "plt.axis((0,10,0,8))\n",
    "\n",
    "# 去掉坐标轴\n",
    "# plt.axis(\"off\")\n",
    "\n",
    "plt.plot([1, 2, 3], [1, 5, 7])\n",
    "\n",
    "# 让x与y轴具有相同的增长度（比例相同）\n",
    "#plt.axis('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xf731128>"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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m0OHAD6cqOqRe4IwVSYOk6um0i4CPA/8BXBYRe0TEHuVriyNiqsGvXwfOi4jn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\nHpIkqWMsPCRJUsdYeEiSpI75/978q2qtRKFeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf7c9160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置坐标轴的标签与标题\n",
    "plt.plot([1,3,5])\n",
    "\n",
    "# 设置xy轴的标签信息\n",
    "plt.xlabel('这是x轴')\n",
    "plt.ylabel('这是y轴')\n",
    "\n",
    "# 设置标题信息\n",
    "plt.title('这是标题')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 通过绘图对象设置\n",
    "除了通过plt对象外，我们还可以通过子绘图对象来设置与获取标签与刻度。\n",
    "* ax.set_xlim 设置x轴刻度范围。\n",
    "* ax.get_xlim 获取x轴刻度范围。\n",
    "* ax.set_xticks 设置x轴显示的刻度。\n",
    "* ax.get_xticks 获取x轴显示的刻度。\n",
    "* ax.set_xticklabels 设置x轴显示的刻度标签。默认显示的是就是刻度值。\n",
    "* ax.get_xticklabels 获取x轴显示的刻度标签。\n",
    "\n",
    "也可以设置标签说明与标题。\n",
    "* ax.set_xlabel 设置x轴的标签说明。\n",
    "* ax.get_xlabel 获取x轴的标签说明。\n",
    "* ax.set_title 设置标题。\n",
    "* ax.get_title 获取标题。\n",
    "\n",
    "说明：\n",
    "* 如果需要设置或者获取y轴，只需要将x换成y即可。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.0, 100.0)\n",
      "(0, 120)\n",
      "[   0.   20.   40.   60.   80.  100.  120.]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xc48c6d8>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6LLrFlALT5mibMtGWzETdZGLLFuCMM/pXmdi/vxplYnERePBB9/PLy8Ajj4R1\nV2XkB5OJTMipTNQRwExtWiVEb1AlYnDwYK+S46KL1IXclZkgZSJnANNcXh3KxP/6X8Cznx3eC8AF\n2/dRpEzonyW0fNAG3eaoS5moIzOxsJD3glI3mTjrLHWe9KMyIWV1mYkPfxj4yZ90P9/pKHJd1v5j\npIHJRCak9pnQE+4pTatylYaG2hxjY72KDX267FtuUfMJbNmitsWlTOSyOY4eVa20m1ImHnlE/bZ1\n+oyB7fuYmVG/XZkJ/TsuM3DqNkcdAczFRTUhHVAtmQDydsGMIRNl54AhMtGvmYkjR9T+qkKZmJvz\nkxH6ntjqaAZMJjKhjM1BF5KUToSpAczUag79okcd7g4eVGWhF1yg/p+edmcm6rA56lAmyIIoq7DY\nvo+ibV5e7k0bXiY3odsco6PtszlSAphEJnJaHU0pE7Fkog1Nq2yttAnbt6uxInUfdTr+99LnZzLR\nDJhMZEIOm0MIdbGuOoA5PLy2Ox0QrkzQxYfes2VLT5m48EL1uItM5FImpGw+M0GKQC4yoZO0Irtr\neRk48cS125ECs5qjTpsj5A4+ZW6OfiYTUqoQs25zFHW01dfXBmWCyK1LmdBfE4vlZf+xwMpEs2Ay\nkQk5AphA/B0ivZbk4xBlwrQ4gPDMhPneE05QJ++ePWuVCVdmYmpKfcYyA9/iovLEXdUcunXUdmXC\nFsAsIhOdDrBjh/o7p83ByoQdoWRieLjccbZvnzpvzjxTqX6dzvruribaZnMUKRP6a2JBmQgXwWJl\nolkwmciEHMoEEH+hTclMmBYHkGZzAGrwvuEG9V4iE67MxPHjivSMjZW7CNOyfTZH1cpEbpvDpkz4\nbI7ZWXXxyqVMDFIAE+hPZYLKQkmZAIqtjraRCTovbGSi7Pwc9Fl95wXAZKIpMJnIhFRlwry4j43Z\nB88DB+yMPKWaw6ZMpNgcgFImrrtO/R1ic0xNxVs5JmxkwmxaVZcyUXTnWASbMjE0pCwvnzIxOlrc\ndjtk3XUrEyl9JmKUCboI9zuZoDxSUUUHfWdCtINMzM2pY5O+Zx1EJsooE/pv1/NMJpoBk4lMKKNM\nmHel5qBw6JCqlPjGN9zrpYtqlcqEy+Y4flx5pCS9+8gEKRO5yUS/KxPmd+Kzu2iW0aLZRYtgBjDb\npkzEZibGxnoXsX4lE5s3q3MqVpmYnm4Pmdi2rVfxpYNyFKnKRNENGysTzYLJRCaUmYK8SJmYm1MX\ny4cesq9GbamiAAAgAElEQVR3dDS8rNRGCICwsjaXzQEoi4MGkKkpd2aiDjJRhzKRK4DpKtX1Xdxp\nnogcZKKuAObKivqp0uYYBDJx1lnqPCIyEapMTE21g0y4GlYBav9MT7tLnovAykS7wWQiE4r8PN/7\nijITNDDaBgt6f2jDK3N9hJDwmMvmAHoWB2BXJqTsZSbGx/ORidFRNfgWKRM5JXxqzANUp0z4bIdO\nJw+ZqNPmoO+7ygDm2Fhv+U31mShLJs48U/1NNke/KhMuuGzcEBSRCbqxYjLRDJhMZEKVyoSPTNBd\namgrbp8ykWJz6MoEwUYm6KKbOzMhhLog1qlMHD3aW14VAUwg3ObI2WeiSmUihUzE2ByksgwPK7Wq\nKWVCyvTum1QWCvQ3mXApE0C5Sq6iG7ZOBzjlFCYTTYHJRCbUoUzYLlymMlFlANNmc5AyUUQmqFNk\njmqOo0d76wHUxaPOzIR+Aa+iNJT+95GJkZHeVOWpqHPW0LqUCcCd2UlFDJnQXx8DKXs2B6C+/8nJ\ncJtjerodTavuuw941KPcz5e5kSi6YVteBk47TTXGagOx2mhgMpEJOdppA+nKxPCwvwLAtT5CqDJh\n2hx0F6KTCVtmwiQTuZQJQJGJOqs5cpKJTkdVb1D3U4Lv+9CrOXLZHG1UJiiwGZOZAPqTTMzNqW0m\nMgGEdcFsmzJx773A6ae7n6/K5lhdVT+nnab+p3b3jPrAZCITcrTTBux3pCGZCSDsRM3dtOpZz1IT\n8JxxRu8x22BO5CKXzTE21vvcPmWCLtI5L5T6BTyHMmEjdyHKRM5qjqoDmLFkYnW11za8aWWCvocq\nyYReFkroNzJx5IhSBXxkoiqbgx479VT1m62O+sFkIhNyNa2yXWiLbA4axEJOVNfFK9Xm2LIFeMlL\n1paCTU+ri7u+PF2ZyBHA1OvYTTKhf0aa5bQKZUKIcDKxf78aaE24ArGhZOLIkbQ7PSmbsTkmJ9V+\nCyGuQLh8r5MJV9O0VNShTNjIxObNcTZH02Ti3nvV7yJloiyZsB0P9BgpE0wm6geTiUzIFcCMVSYo\njAfUo0yYNocNdKHXrY7cNoePTJifsQoyIYRKrYeSid/9XeCP/mj94ymBWDpmyGKykZQi0LLrtjnG\nxsKPNUApE22xOWykT0dZMrFpUy/QDIQrE0ND6hwYdDLhU3/pGGFlojkwmciEpktDXe81UUaZcF34\nTNjK83IGME0y4avmAKohE7Oz60mMD488Yh/gyioTQJrVQfu/7tJQqriIIRNN2xx1KRPUY4IQqkxQ\nNVcbyIQQPXXAhqoyE7TPN21S+43JRP1gMpEJdQQwbRdgurAAYZOElSkNtdkcNtgaB+XOTJjKhL5v\n6lAmtm5VF+JQUjQ/byceLqWoajJhNsuqWpmg/VSXMtFUnwn99THQy0IJocoEVXO1gUycfLJfwcmR\nmfDZHCMjakZdJhP1g8lEBkiZN4CZqkyE2hw5qzlssJGJOm2OqpWJAwfSyATtAx0p1TV6NQeQ1mvC\npkzUaXOE5HOA8CzAoCgTOmLIRFuUCT2IbUOOzIQvgDk6ymSiKTCZyAB9YGyqaRUQbnOUmegrVZkY\ntMzE7GweMlFGmaDMRBmbo+4AZqwyQQFM17TT+uv7lUyYPSYIoTZHlWTinnuAl788rBFXUVkoUF2f\nCVYmmgeTiQzQD+SmMxNVBjBDbQ5bZoL+npiot5oDaI/NEaNMhJCJqSn1ujI2Rz8EMKWMI7r9RiYO\nHlSN2My7+lhlogoy+I1vAB/4QFjIN5RMVJmZYGWiOTCZyAA6kCcnq1UmikpDQ07U3E2rbHApExMT\nKnle9i7q6NHmlYlYMrGw4FYmUm0OIdJ7TTQZwIwlE0BcFqgqMmE2FjORSiZoW+mzErZsUce6j0hV\nrUzQfi8KGksZRiaq6jPBykTz2NBk4tWvBl73uvLLSSUTUpZXJvTS0JAT1ddOu2hegbI2x+Sk+ruO\nao46yIQZ/PTBp0yk2hxA+vwcps2Rqkxcd50qeQ1RDgD1XYWqYEB7yAR1mPUhlUy45meh+Tl8s2xW\nTSZomUXH+YEDSn2s0uaIVSaKrDFGXmxoMnHjjcB3v1t+OXRwT0zEDSQrK+qA1weR2MxEbADTp0zQ\nNrlQxuYwyURZm0O/i7NVc7QpgCmlv5oj1eYA0pUJ0+ZI3Uf//M/Ae94DvOtdYetLyUzo//tebzat\nynUx0fe3D6lkwjU/C01D7rM66GaiaWXiRz9Sv+vITIQoEwsLvTl8GPVgQ5OJhYU8J2CqMkGvLTPR\nV2wA06dMAG4yIWW4zTE8rF5nloYSyagygEmVNVUpE4uLav0xAcylpR6hMC9wsRkWyg/QMZM62Vcu\nm4PUlte8Brj11uL1jYzUY3OsrOS7uMaSiSKVxoRZpksgZcIXwqzL5ig6zkMaVgH1ZSYAtjrqBpOJ\nDCcgHdyTk3EXLRuZKKNMhPaZ8CkTru23qSg+mFKzrkxUGcC07dOcZIIu3DHKBF1wiZDpiA1gmmHA\nspmJsjbH/Dxw5pnq54or3Mugi31oe3PT5ohRJmw2WxlUrUy4bI4QZcIMYOaW9kNtjnvvVZ//pJP8\nr6urzwTAZKJuNEomhBAXCSG+LYSYE0K8LfK9nxRCFIirfuRWJkJnOCS4lInU0tBQm8N1J0zLs8G8\n+BTBRybK3EVJ6ScTtru8nGSC8glEJkI6YOpZCTM3EWtz6IMmkJ6ZsNkcKXeMCwtqGz7yEeCGG4B3\nvMO9Pr0MNdbmiFUmgHyNq+qyOcqQCTqGcodoQ22Oe+9VU48XhVTr6jMBAA8/nLYeRhoaIxNCiDEA\nnwdwPYBLAVwohLgi8L3PBPCzAP5bmW1oqzJRZTvtVJvDvPgUwexCmCuAubSktrGITFSlTJhkIuRz\n6AOxSSZiO5Ka80TkquYYHe2pTzGg7/UpT1GB5je8AbjppvWvSyUT/aRMpM5Q68pMxNoc+rJyIcbm\nKLI4gHI2R2ifia1bVdUYKxP1okll4pkANgN4pZTyLgCvBfDSojcJIaYAvA/Af5VSenLOxVhYKD+F\nNJCembANIuYdKd2Jj46GzRpalc3huntywZy50ZaZSJFkaZmuag6bZFyFzRGTmcipTJg2R2pmwvw+\nU/1+nSS+6U3AeecBr3qVfX1lyESKMtEvNofr3JqeVhfFUJtDX1YuxCgToWSiamVieBjYvp3JRN1o\nkkxcDOBbUsoFAJBSfg/AhQHveyOAUQArQohfFKKoYMuNtigTvnbaCwvqojs7W1waWnbWUFqeDblt\njpBGRDbYyARV0eihu6qViVxkIrY01FSzZmcVUYslxbYOmPryQ2FmYZ7+9F6yX0csmVhcVPkKWvYg\nkwlXZkIIpU7EkIncNkdMZiKETKRmJvTxIuS84F4T9aNJMrEZwF3GY8tCiC2uNwghzgDwRwDuBHAO\ngLcB+IfUDWhjNYcZpKIBcevW8jYHBQBds4YCeW0OH5nQlxkDF5kA1IBXtTKxf79a9/h4Gpkw7/Bi\nm1bZAphAvDqxuKi+c/reaRti95P+vQLrFSmCXgkUqkyMjYUfK/1MJlw2B6ByE22wOXzKxOoqcN99\n1SoT+rgaotgxmagfTZKJZQDmULwIYMrznisAPATgF6SUbwbwVAA/LYT4xdiVS1mNMpEjgKmzcBoQ\nZ2eLS0OLlAlaZooykWJzuDITdFHJTSb077NKZYLmxMhlc8QoE7nIhFnmm0OZANwzduoX+9ApyHUy\nEaNMkJ3Wb2TCdhwUtdRuQ2Zi7171uiozE/o+9fWZYGWiOQScIpVhP4DHGY/NAPCdDo8CcLWUsgMA\nUsqjQojbAZwL4GrXm6688kps2bJW8Hj+83dhdXVXVmUitmmVS5mg50ZG1pKJ22+3LyNUmfDdARUp\nEyk2h34ym5kJfXtiQI1oXGSiDmWCyERoB8yiAGZKNYducwBpyoROJlKViYWF3v4H3N0n9YZnMcoE\nbZfvWFldXdtbpN+UCZfNARRP9tXpADMz1ZEJWp5PmQjtMQHUq0zYgsAMN3bv3o3du3eveexQ0eQw\nGpokE9cDeBn9I4Q4G8AYFMlw4T4Aj9XeI6AIxv2+FV111VW45JJL1jxGLWpzl4YuLytlISTJ4Qpg\n0nOTk727PJfNYTat8rF+36AVqkzktDlSwq+pykSuQfbAgd4FvMoAZqjNkTpzqNnNNJcyMTWlvoeV\nlbVlgimZifHxMGXCPK7Hx1VwsV/IRJHN0XZlIrT7JdAbo0LHSHM7zL/Nx1iZSMeuXbuwa9euNY/d\neOON2LlzZ9D7m7Q5vgZgRisHfQ2U6iCFEDNCCNvp+ykAvyKEeI4Q4jQAb4UiRE5VwgVi2jmqOXSb\nAwgPFtou7ubgqSsTZdtp+wat3DZH1ZkJvZ02EZy6MhO6zdHpFE/PnDOA6bI5YntNmDZHrswEkTzf\n5xwZCZ8FNESZMI9NIfLOz1EXmbCtIySAOTLSbGbi3nvVMbBtW/HyUoOi+ut9NsdQ94p24onAvn1p\nIW9GGhojE1LKFShl4n1CiEcAPBvAn3Sf/h5U6aj5nlsB7ALwBgC3AfhlAL8ipbRMoeSH2ZegDPQA\nJhB+orgyE/p2mZkJWzvm0HbaPkKQ2+YwMxO5bI62ZSaA4s9RRdMqes/kpNqOsjZH6oXQRSbMC3lK\naahOJkJIsn5surIbKQglE3QhS7E5qDuoiaYDmCHVHFTJEaI0pJIJfZ+6SDbNpAsoMiElMDcXtx5G\nOpq0OSCl/IIQ4hwAO6HKRA90Hz/b854vAvhi2XUTmVhdXS/JxsJUJkIHk6LMBLCWTFAwUx/YzFlD\n+8HmKBvA1Dv+Ac1lJuhzmLkBE/Pzan/YJvvyleqG2BxAWuOqKm0OIB+ZCLn4uMhE3cpEaKtwEy51\nCgi3OUIUnBSEKhMhFgewdjv1G4LQ7QDcyoT+HekttelvRrVofG4OKeVeKeVXiEjUBXPK6jKoS5nQ\nH9eXkcPmKOreV8bmoP4PuWwOcxBqWpkossoWFtRnn5wsH8C0kYmUxlU5bQ4zgAmUJxOknKTYHLQd\ndZMJIJ1M2I4BIL7PRBOZiRgykbqdIQFMfR/y/Bz1IxuZEEJckGtZdSAnmTCViTJkwqZMjI72MgLm\nSR0za2iIMpGzmmNpSW0f7etcAUwfmahSmVhdBQ4eXBvABIo/B92928hEbGmo7ZhJmZ/DZXPEKBNS\nquXYbA7TYkjtMxGyXYNAJnzKxOHD7m6xdTWtyqVMVEUmfMoEox6UIhNC4YVCiO8D+Jav4VTbUKUy\nETqY+Ko5dDIxPe0+CesOYIbaHCR3Hz/eu7DkykyYZEK3G6pUJg4dUoN6rDLhIxM+ZWJ1dX24M5fN\nYV7AUpQJkyQC+TMTQqRlgfqJTLgIJaDIRKfjvpg3rUwsLwMPPhhPJlIzE64uw6YysWmTuslgMlEf\nksmEEOK5AG4G8BYAHwNwrpQyvCi1YeiDetmKjrLKhG1Q120OH5nIpUyEdsB0ybEm9IsK7euqbQ5f\nNUeOOzZ9ki8gjkxMTKwnE1L6S0OB9QNnzsxE2QCm+b0C7sxESp8J2r5Qkqx/565OnClo2uYA3CHM\nsmSi0wFe8AJ7C3R6HnAf4w88oAhvSmYidjsB98zMpjIhBJeH1o0kMiGE+G0A7wfwQQDnSSn/u5Ty\nkaxbVjFyKxNC9Aa/3AFMat9sbisFMvUApm/OizLKxOKies1Q4BHTBJmoWpkoQyZsygRtk8vmANYP\nnC6bIxeZiCFdNjLhszliMxP0+kFXJopsDsCdmyhLJvbuBXbvBr7zHfe2AW5lJKZhFVDe5nB1GTaV\nCQD4jd8ALugr872/kVrN8TEAn5VSHs25MXUiN5kYHY0fkOl1eiVJkTKhX7jo/Xo7bXrcVp1Stpoj\n1OIA1pIJ8ntzVHMcPbqeTIyMqM+7sLBWpdGfz0kmKDOhKyI+6BUPOpmwEQOCy3ZwBTBT+kzovTpS\nbI4YZSLF5qBlFVUp1UEm9M/oQ26bg5QJF5mgsSf1jp+OXdf7ipSJmIZVQB4yEVLNAQBvf3vcOhjl\nEEwmugHLJQBSe8xWdCMBPJTS+6FO5A5gjozED8h0V6HXZ7uUCdtJqE+7q/9eWrKXKpbpM+G7e7JB\nz0wQmciVmdAvgoSJCfWdUmhP36e5yATd/adWc9DfhBBy51Im9IFzZqbXZjwUi4trmwylKBP0WfRj\njRoo5SATJ5yg/i5qwVw1mbBdqFzIbXOQMlFkc4RkS2wo6rdTVBp6771qG4n0FCFHZiJUmWDUixhl\n4iYoMlHUU2wYAIQQPyml/PfUDasauZWJkZH4Adk2iMRkJsw726IGP2VtjhgyoSsTdGHPVc1x0knr\nHycyIcT67RwdzadMjIz0yEyMzUFESlcmfN+H67s0CSTQaxAW06LY/D5zKROAvWFUamkobVs/NK0C\nmrM5ADfp2rNHEWAiwTqKlImiplX33w886lH252zIkZkIVSYY9SI4MyGlHJFSTkkpZwp+pgBcC+AZ\n1W12eehkIkcAU5caY2wOcxApykzo22pK3kWsv2wAM9XmMC86w8Mqe5ErMwGobaPMhHlxzmlzbN3a\nu2CXDWD6vo8iMqEPnFNTKgQXsz/N7zNXABOwqwKp1RxAWgBzUDITRTZHCJl43vOAd7zD/v5Qm8Ol\nTBw5Eq5K0Db61udCUQCTlYnmkRrALLr/+RiAL6csuy5UqUzE2hw6cigTRXcZqaWhqcoEXXTo7hxI\nnz3QZ3NQNYe5nbnJBEEvSfXBFcBM+T5sOQtbHqMIVQUwAXslhU5eYqYgBwY/gOnLTIyOqv1rszmk\nXN8B17af5ubcZKRsZsLsgFqEsnNzuGwOViaaR2pp6K8KIX4ohHitEOJM80kp5d9JKb9XctsqRe7M\nRKoyYV5IUjITOZSJ3DYHDTB6nwl90Bkfz6tMkM1RtTJB4UugfDVHSADTpUzoVTV6PiUUVdscbVAm\n5ueLJ2ELQSyZiJ1cypeZANxdME3Ly7Wfjh93E95Qm8P1ft3CC0GqMhHbZ4JRP1LJxA0A/i8ATwOw\nRwhxtRDi14UQjbfnDsXCQu8kyKVMpAYwdbiUCduFK6cykdvmGBpSJz4pE0ND60tgqyATVSoTBw6s\nVSZCsx+udtq+QKyPTJgB0xQy4bI5cigTtrxCbJ8JMzMRq0yk7BMXmrQ5APdkX+b57zqnjh93H6Mh\nygSpfjYcPx6nTFTZZ4LJRLNIuvhLKe+TUr5LSvlzAB4D4HoAfwvgCu8bW4SFhZ7Xl0uZSCkNNU+A\n4WF1oQhRJsxkf5EyQiWjtl4RIXNzxCgTQO8Ole7MzaqVXO20gfqUCZ1MUNgzVJmYmAhXJnw2h/n6\nHDZHmQ6YZuWQqUxIuV6ZCJ2CHAhTJoaG1pZDuzpxpqBJmwNwT/YVQiZWVtT3VIZMzMz4lYkUmyN3\naWjMd8SoBqWVBCnlXVLKPwVwFoBPlN6impCTTKQqE7YLtFniFVMaWmRz+OTUoSH1k8vmAHp3qDYp\nNEWZWFpS29eUMmGSCUBdkGMCmKGloUXKhI5UZUJfb8r02fPza7NC+vboF/GVFUUoUm2OEGXCVM36\niUyk2hwhZIIIZhmbY2amPzITrEw0i2y2hJTyQNt7S+hYWOiVXeWq5sihTABrS+FyBzB9hGB4OJ/N\nAfQuKjYpNIVM0IXBVc2xuGj/jFVlJgC/BExICWDGkIkcygRNnx1rc9guJKbNYdoQKWSiSJkwv/Om\nyERIuNRElTYHfQ8pygS1e8+pTKRWci0vq/e6jgVWJppHajXHaUKI93qe/69CiFnX823AwoIacITI\nr0yUJRMk69LP9LQ6AUdGypeG+gYt3yCfw+bQkUImqDFTis0hZbkwnpRpyoSUxQHMmECs7ZhJDWCa\n5DC2H4ePTOgX8RQyoW9fiM3RFjJRhc1RRpkoQyboxmLTJrUu2/kTG8Ck7U2xOeiGzdVngpWJZpGq\nTGwC8Du2J4QQzwDwFwCemLpRdYBCcalBQB05S0OB3slm3omb25rStMp3wvmUiVSbw0UmUqo5fMpE\nkc0BlFMn5ufV9saSiU5HEQqdTFBH0FzKRCyZWF1Vy7HtpxzKhGlzuMiEa1ptek+MzeEiE4MSwPSR\nCf1mwtxP9D2k2Bz02MzM2tfqiA1gurazCHrFHCsT7UQqmTgOYN2hJYQ4HcCHAbxbSnlNmQ2rGgsL\n6gKUg0zkLA0FendiRWTCVCaKbI6yykSszUFy9/HjeTITIWTCpUwA5ciEOckXoYhM6BUPNOjS61NL\nQ8vaHLTfq1QmbDYHrY+236UUrayon5gAZj8rE0Ukvymbg5bvIxOxNgdtZ0pmwkcmWJloHqlkYgna\nHB3Aj4nEPwP4FwB/XHK7KkdOMpGqTLgGEZcyYV64bIOJ/njo+gi5bQ66Q3XZHLFZFbq7sg1eVSsT\nZckEBTD1x3yloTE2x/i4sutC78Jpe8tmS+gcMhFicwDudZn2Txllol/IRA6bw7af2komUjITRTYH\nKxPNIksAszsl+XcAfFxK+VtS+gTMdkAnE7kCmEIoq6BMO20gXJlwlYamKhN12hwpA4qrFJEeq1KZ\nOHJE/Ta7b1Ibbxd0ZUKfKh3Ip0wI0ZufIwQuZaIqm8MkLyEN0vTtS1EmXLOXpqDpzMSWLSovZJ6b\ntpsJcz8VkQnfRF8mmTCP85UV9ZpYMpGamaBcmsvmYGWiWcTMGvoMAIcBHAQwDWBYCPECAL8PYBzA\ns6SU365kKysAkYnUTow69MEmRioum5lwzRpalTKRYnMcO6YGdvOOPoVMmBcZHaQQdDrrLZUcZILW\nbRKZGJuD+mzQY7lKQ2n5oTaHaz/mtDkWF9XFZng4XpkwX5+iTAwPq8/XD2QipDQUUISCKtAAO5kw\n7ZAqMxOupmVFKJOZYGWivYjZ/X8N4EQAqwBGoUKYHwXwAICX9RORAKrJTABxd3fUXc5ErDIRanOE\nKBO5bQ7KTJx22trnUgZ6H5nQlQl9wAXykglz3WXIhC+AGWNzAHHKhM/myFUaCqjtmZnJQyZilQna\njn4hE75zS7fHishEFTYHqXEmIaFlx1ZzVJGZYGWiecTMGnq+lHJWSrkNquvlQQDnAHg7gPcKIa4R\nQpzmXUiLUEVmAige+HTEKhPmhSs2gBmiTLTZ5gghE1VlJlwWSxGZ0HMeZmai0+lZYyZilYkcNkdO\nZQLoHb+xZMIkOyk2B21HP5CJIpJv2mP6+4DmAph1KhNEFmh8NY10ViaaR2pmQgKAlPJuKeW7AZwP\n4JsAviuEeEqujasSVSoTZQOYqcpEUeOhojugqmyO3AHMImWiisxEDmXCFsCkrI0JVwO0Km2OWGXC\nFcA08wqpykTM3BxVkYnVVfXTpM3hqtYJIRM5bQ5zGalkokxmwlUJxMpE88jC5aSUywBeI4R4GMCX\nhBA/IaW8I8eyq0JblAmXX07KxNDQ2iCarzS0aP1lAphlm1blKA1dXOy1Gzehk4kqlAnXBXhiAti7\n1/0+vZrDlpmIbW+ew+ZwVZHEXghDbA7b+kLmgdFfX0aZKNtngs6HqsgEdZmsWpmg3iLm5+gXZcJW\nfq8reqxMNI9UZWLM9l4p5bsAXAPgY0LY7rfaAz2AWbaaQ2fFuQKYpExQl06guDSU/i5jc+Scm2Nq\nSi3v0KF8NgeVQZqYmFAD5vx8NcrEwoKdyJRVJnz71EYMc9gcdQQwgfXKhNlnosoAJm1HWWXCRth9\niCUT9NrQzITtvSFkArAfp2UyE2XIRJnMhL5tBFYmmkcqmZgBYBE4AageE0+Co0NmGyBlfpuDBpvY\nAGaRzaE3aHLZHPosoL4TtYmmVQBw8GBeMmEDPX7kSHXKhI3IxJAJW2mobwC0kQnXHVhVNoeUwJe/\nbO9W6SsNBdqRmaAW7Kmomkz4eo0QcigTtvcD5ao5aNl12Bx6nwn6XwcrE80jlUzcAmCb7Qkp5Y8A\n/CGAT6ZuVNWgAE9VNkfO0lAfmaATTL/AlVEmqrA5CDnaaS8suMkEDbiHD1eXmfCVpLqwsKDI3uio\nPYAZS+5cd2A5bA7bsXvDDcB//I/A97+/fjmhNoerz4TvWAPKZyZmZvqHTFSdmQDSlYmizERKNUeZ\nPhP6thFYmWgeSWRCKvgExP8ppSx5GlcHPZnfdGloWWXCfH+ZzIRrIHTN5VAEfdttmYlYe2lx0R74\nA3qPHz1aXTWHbd0hTauoLHR0VBE2M4DpQt02h+3Ypb4F1AFUR1XVHLlKQzdt6jUbS0U/KRO+DphA\neZsjZ2Yi1eZgZaK9iCITQog/F0JYCtnWvGYUwM2ltqpi5CYTqQFM18XEpUzYSkPNE8h3ooYoE7aB\n0FVKWASdQFRtc9CAK2W7lIn5+bUkRLcjisidy+awfYe5bA5zHxEhsM0NEVPNoZfAxpKJVJtjZqb9\nZMLXuIwQo0zYOmBSb4pUm2NiQn2unJmJHAFMHaxMNI9YLvciAK8XQvw+gB1QDaxMCFgmAWsTTDKR\nq502EDeYhLTTTlEmXCdqiDJhk55D7p5s8NkcVZEJWraOpsmE/tn1i35KIDZnn4kQm4OWaZIJyh3Z\nLiTUfVKv5hgb69lxsZmJ0VGljlFHTdvnGWSbg447mzIxPNzbry6bY3ZWhaBTlYnRUXV+2ZSJ4eH4\ni3hqZmJszE0mWJloHrE2x4qUchXAiwHMA/gDKOLwcu33AoxJwNoGnUxU0U47Z9OqosxErDKRYnO4\nOiYWocjmqCIzAVRXzeGyOVLJREoA00cmYpUJ236y3dkC68mEb9I1YG0lhXncxfaZKOrsOug2B5WH\n25QJ/Tt0BTCplb3tOF1YUNvsIxNjY3Y7L2WSL9d2FsHsM6HvYylZmWgDgsmEEOIs7V8ppXwbgEPd\n33PG79aXhQLVZCZyBDBdyoStNDQmM5EawEy1OXIHMH2ZCX3b2qRMmHfvpjKR0+aIyUzoSoG+vlBl\nokjizkEmdGVCf9z2ep/NUWbaQbP8sghV2BxAr4+K+V6TTJCCQygiE4uLa1ue69BVE5sycfx4fPiS\ntrQjKB4AACAASURBVDNnaSh9XiYTzSKITAghNgO4E8CZQogHAFzUfUo6frcaVWYmcgQwQ5UJm7RX\n1ubwZSZS+kwQbDbH8vL6TnY+hNocLmUidgALWff4uFqu63OYd2/6RSFEmajK5rB9lhhloohM6DOH\nmusLIRN6xiJVmZiZUReaMjZmijLhqlKxIfTcsmVibGRCXyagvr/ZWfW3KzNBZMLWohpQ62iDMuEi\nE7HfEaMahCoTR6Dm47gfwPMB3FvZFtWAKshEijLhUgpCMxM2aa9MADO3zaFPbmUjE7RNoWgyM+Gy\nOegx1+coE8C0Xdx97bQXF8PImWs/2o5dVwAzRJkwMxOEkMyE3tOjjDIBlLM62pCZANzKhL5dtnPq\n2LEwZQJwV0gI4c5MpJCJ3H0mbM37GPUjiEx0S0H3AFiWUn4DwGEhxFsAbO/+Ptn43WqFogqbI1aZ\noJ7/Re206wxg5rY5hOipE7bMhL7sEDSZmfApE/S8DWUCmDE2B+3fkNyE6+JruxAWZSZctpNuc5jd\nU0OUCf31ZTITQLvJRKjNUUaZCCUT5rmoH582O6+JzAQrE+1FbABztFsa+vcAOgDeBRW8fJ/xO7UZ\nVi0wA5g52mnHBjB9bJqWcfx4fGlomcxEbpsD6G1/LmWiqM+EvmxCLmUiN5nIbXMAYVaHixhVaXOU\nIROuBL/r9YQcygSts8kAJhCemdCXCfhtDin9ZEJfvm39ZchEzj4TrEy0A8FcTgjxBwB+H8CqlPJ9\nnteNAvi9DNtWGapuWhUymPhOANqmxcV4ZaJMO22XMpFqcwC9i1zVNof+uE2tAcorE3SHZ1uvi0ws\nLKx93+Rk7+K2tLT2+zURa3MAYcpEjM3RVADTRiZsxwpdEH1kokx5aOxdL/VqkdI+h4yJUJsjRJkw\n9xPlRYhMmMcobWcImbDddB0/3o7MRCzhY1SDoN0vhJiFKgPdDuDDQoiHCpb5gQzbVhna0LSqSJlY\nXFSDR2xp6Oio++60rDIRa3MAbmWClpWLTFDLahthqsPmcHXBtCkTNMtoSmlokc0Rokz4bA5zfWUy\nE/Q5UzMTBJ/NsbKiLohtykwAysK09cQwUYUyQfuJjoVNm3pjig7632dz0DJdykRKNUeZzITP5mBl\nolkEnSJSygMAHiuE+AkArwPwKgAPAfiM5eXDAFr9teozQJYlE5R9yK1M2PreUzkl3fXEKBMhUx1X\nZXOMja0fWGlZMRaTLzMBqAHPtk+KprwOXberzwTgtznMACYNyiGloXXaHDmVCZ/NETIFeagy4Ts2\nm8pM0PtCyESVmQn67qan7dUYRWSiSJmYn7erdUXI3WeClYl2IGr3Sym/DeDZQohfBPBBAE8A8IyC\neTpaB7owCNG7+IbKkibMwSZUmfANgvoAYSoTQI8UuEpDY+/gCFXYHNPT9gtO7swEoJ6zzRo6NKR+\n2hDAnJgIz0zUbXOkBDCrqOaICWD6zqMmbA79s4UoeTHVHCYpCiUTU1N2MkD/b9689n225U9MAPv2\nrX2+icwEKxPtRepEX1dDTTP+zn4jEsDau8yUi5oOU2EILQ0tUiYINjJB22orDXVJiCGDVhU2x9RU\nXjJRpEwA9s8YG4wLXXfZAGauplVV2Ry0PPNCRp8hpJojts+EmYFIVSZGRuwX4RiUIRMhqLLPBO3/\nqSl7aWeMzZG7mmNlJa4fR0gAk5WJZhFNJoQQ40KIL0opD0kp/8HxmrcKIS4tv3nVQJeeU7x7HeZg\nE1oaWpSZIPjIRIzNESKnFk30lapM2HzVKslEaNljDMrYHDlLQ5uwOTZtUhcmffCfn18rO5vwBTCH\nuqOObwry0MxE0bFZtqV21WSi01nboMuFlGoOU5koa3OY708NYBZV59jAmYn2I5pMSCkXAfySEOJ7\nQoivCiHeLYT4TSHEdgAQQjwXwP8JwDLPYDtQtTJRlky4lAnzwuUKYJZRJuqyOXIHMIFqyUSqMuFr\npx1ic4RmJmJtjpgA5kknqb/1i3LRXamemTDXJ4T/+4gpDS0iE2VnDq1DmRgbK7ZYc2QmYpUJ0+bI\nqUzY1ueDr88EKxPtQOrufwjArwM4FcA5AH4ZwLuEEP8bwM8A+DUp5W15NjE/cpIJmzJR1uaIUSYo\nZKa/JlWZ8NkcQ0NpJ+vTngaceur6x1ObVvkyE3Rhr9PmoO2xkQkp/R0wQwKYoTYHDeqhNod53ND6\nbMrEox8N3HGHyk2ccIJ6vOhCMj2t1rO8bP+cKWQi1uYAys8cWgeZCLmjtikTps0Za3PQ8nxkQrc5\nclVzFDUhs4GOe1t4l5WJdiCmz8RrAewFcDVUJ8xbAdwqhPgGgH0ALoDKUdwD4NoKtjUbqiQTsQHM\nspmJ0ABmiDLh64CZokoAwK5d9sdjqzmon0A/2Rw0Z4epTCws9KprctkcIyNrq4B8iA1gnnyy+lsP\nYYaQCXp/LJkwlYwyNkfblYmi3AyhjDKRanPoRKcNysToaE/VYmWifYixOSSAXwXwXai22f93l0jc\nDqVSvF5KeQ4U2fj73BuaE1XaHLHKREw1h3nhimmnXUaZcMniZRC732n7mwhgrq6q9cfaHLbySfp7\ncTG+VNcsQzYROnNobADTRiaKVCK6Yz12LE2ZsDUhS1Em2p6ZCCXqZTITOWyOnBN9+b5PG8zj3iTZ\nrEy0AzFk4q+klM8CcCmAt0O1zX48gM9IKV8gpfzH7uveCuB8IcQz825qPtjIRGpL7VRlItTm0GVE\nm81hDnIumyMkROmzOVIqOXyIJRP0/TShTPiqWXzHj41M0DbOz8cHMIsubKEzh4YGMDsd9f8pp6j/\n61ImcpWGAu1XJkJtjpgOmHrTKsoZpFRz6GTXfD8dG3UoE0VWMisT7UDM7n+LEOIJUBbGKQD+EsA4\ngH8SQnwfwEcAfBTA1wG8AopstBI6mShbzVFlaejkZC/5rj9eVBrqy0zUbXO4EDugFE0spT+XW5nw\nrZt6ldg6YNp6MehBydjS0BAyEWJzuFL4tI+o5wp57mVsjlRlwtaXIjUzcd997u0swvKy2hdDgbdd\nVSsTej+ckNJQuhlJUSZ0omMqE0VNy3yIzUwUhdxZmWgHgpUJKeUrAbwZwEEAK1Bk4v1Syq8A2AHg\nNAC3APjfUsovSin/3wq2NwuqDmDmUibMeRvMu+AYm6OMMlGFzRErdYYoE/RcbmWiaN2uyeJsvRh0\nMhHb3ryIEIbYHFKqi+ujHrX+OVouEUpa1oknqt8xZMK0Ocx9F5OZoG61TZWGxtzxVpmZILtNf69+\nLAwPK9Kj2xw6mShTGkrKhOzOB23r0BuK2HO/yEpmZaIdiAlg/huU2rAFwAkAfgTgbUKIKwEck1K+\nQgixFcAvCyEullJ+r5ItzoCFhd7kN001rQoJYJpkwlRRbANdkc1RpEzUZXPQHX2ovRRjc+RWJsqS\nCZ8yUbfNsW+fes1ZZ61/jpZL9hkta2ZGXZTrtDnMfZ1KknPYHFWSiZhqDkCNXfqdva3PjE4m6Hvw\nKRNU2VNUzaE/lkOZiLU5WJloN2IyE38E4LVQbbRPhCITrwTwtwB2CCFeBNVe+7kA/iZkgUKIi4QQ\n3xZCzAkh3haz4UKIkW6vi5+NeR/QLmXCF8B0KRO+plV0otEdRMj6CK4+E1XYHLQtVWQm6rQ5aJti\nycTRo8XtzauwOe6+W/32kQlaj14NsHlzus1hU7ZibA4gPQuUozS0ajIRqkwAa7/fEDJByoErM0El\n37Zz0azmAHrnQhM2hyuXFmLhMqpHDJlYhJoNdALAbgAzUOThEgALAJ4G4B4p5bUA9gshft63MCHE\nGIDPA7geKtR5oRDiiojt+S8AHhfx+h8jZwDTpUyYF/Oi9+lwKRMhpaH0GnMwK9NOuwqbA4gjE6GZ\niaEhezfBtikTdGGu2+bwkQlarkkmpqfXk4miao6cmQnatqYCmG2wOcyLOb3XRybMzITN5tCtwaJq\nDnoPUK8yUWRzxIZkGdUghkycBuCFAG4FcATAbwJ4NYBtAFaklL8N4De6r/0EgLMLlvdMAJsBvFJK\neReU6vHSkA0RQpwHpYrcHbH9P0bOAKZNmQCK+86nZCZCS0P15Zvr8w1cvgBmbpuDtiW3MuH6fFWS\nCdtdH+APYNKFObcyEUImtmzpNZ/SodscwNqmR7HKBD2XQiZs5DXV5ti0SX2eMtVabVYmbDcTMTaH\nflNVVM0B9I5pOs7qKA0tCmByZqIdCN79UsrPaf9+DgCEEE+VUu6jeTiklHSof0JKWTSNy8UAviWl\nXOi+93tCiAsDN+f9AP47gGeEbr+OKmwO/UAH7Ce6jhzKhG0d+omqh6PaqEzQlOohCCUTrs/XpM2h\nv4/+DlEmYsnE5CSwd697eYAiEzZVQt+WHDbH8LD6rC4y4crnAHbympoFonDhkSNphLiNmQlCDpvD\np0yY1Rz0HqDZzIRpJS8v92YGZjSHUrtfSvlg9/d9xuMh88FtBnCX8diyEGKL701CiJd03/uXABIm\nDV87X0KuAKbu5wHFg0mnowZUW09+lzJhMnpbaajLjyzbTrtpmyOETDz5ycAzHPSybTbHoUPqd8z3\nUWRzhCoTLjJhKhNlyASgjl/X50yxOVzKBHVGtKHsNOSpZCJ0RswqMxM5bQ5XZqKOdtq2MdY8Lzgv\n0Tya5HLLWN+LYhGA8/AUQuwA8BYAL5GyKJXghq5MxEpuJlw2R9GJ4rsjcSkTVCKn2xwuZcJcf0hp\nKGUNVlfXv7cqmyNUfg7JTDz96cAnP2l/LgeZSFEmqGqFEJOZqMrmKCITOZQJet+BA+rvKgOYvmNa\nVyZS0JbMBO3rImVCP2bM0lDb3BxFZMKs5mhDZsJmc7DF0Tya/Ar2Y32AcgaA7xD7awD/Q0r5/ZgV\nXXnlldiypSd4HD4M/OAHuwDs+nGaOWdpKBCmTLgGEZcyAay1BlxNqwD7wKA/b4M+EOrbtriofPbc\nyK1M+JDD5khRJiYn1941j4yoH7pjLyITUqq7XN0W8NkcvmoOKeNsjmPH1GcbHrYHMEOUiYMH1d9l\n+kzQtrmUCd/FmMoe20omlpZ6hMcHvXMqIaY0NJfNkaOaI3efCds4yIjH7t27sXv37jWPHaKBKgBN\nkonrAbyM/hFCnA1gDIpkuLALwGEhxB90/98E4ItCiD+XUr7d9aarrroKl1xyCQA1oA4NAT/1U73n\nY+6QTaQqEz5pzkcm9JPeNZjY1r+01Gtq44I+I58+QPeLzeFD1TaHrQOm6+59cjIsgKlfmIaHy9sc\nvh4T+vpsd7Y2ZcKnEgHq+PUpEzYrYGVFKWMxmYkQZaJum6OqAGZqZiKXzUHnArXqTlEEYslEUZ8J\nVibyYNeuXdhlzMx44403YufOnUHvb9Lm+BqAGa0c9DUArpZSSiHEjBDCdnicBRXcfEL35waoCpD3\nh66UDmB9IIwJAppwKRNlyARlKYrIhGvWUMB/l+GCy+9tUzVHKqlpwuZwlU/qZKJImQB6x1JZm8NX\nFqqvT7c5bGRCyjBlIsXmcNlxvtLQqm2OmLveqktDy2QmVlfXbldKaaiuTKSoEkCvt0WuPhOsTLQD\njZGJbkjzZQDeJ4R4BMCzAfxJ9+nvQZWOmu/5kf4DYB7AQ1LKw+ZrXbB57zEXNRMuZSLE5nCdAEKo\nk5ckWh104SL5OyaAWTRouba9DdUc1PkvNbFd1uagAdCGIpvDRKgyEUsmyOZwpYmKyESIMkFEgtbn\nQ5Ey4aocsr1+kG2OqvpMmNUcwNrjNMTmMEtD9cxEKplwrc+FkHbarEw0j0a/AinlF4QQ5wDYCVUm\neqD7eFGPCnr/fwh5nX4C5iYTrmqOMgFMAPj4x4HLL1//OG2rq7baF8AsYu9kc9iUiapsjph22mXU\nkbLKRNGcIDFkYmIivGkV0NvuEJtjZcVNHH09Jmzr0z33zZsVkaBST6AaMuFSJlJtjrEx9VMXmdCt\nwhCEloYODWFNG2vXdPS+PhOAOk7psbLKREolB8FFDm0ImeiLlYnm0Tifk1LuBfCVKtehZ0iqUCb0\nEs8cAUwAeM5z7I/Ttrr60fsCmKnKRFtsjqbIRFG3xxRlIqQ0NMXmoPW6yIRLldDXpwcwdWUC6KkT\n9Dl8KEMmYubmKDquy7TUbks1B6D2N41fLmKpjw96rxmTDAB+MiGlPzNRpzJh6zOh23msTLQDG6LN\nBw1ogJtMlGmnrZ/QOQKYPtC2upQJXwAzVJmoy+boFzJRtG5XB8wQmyMlM+Frpw24cxNFZKLI5gDU\nHX6ozTE11eui2ZQyAZRrqR1LJoaG1I1FbpsDUMcZKRNFZEIv66X3AuE2x8rK2rljRkbUZ9M7YJYl\nE5yZGCxsCDJB5WmAnUyUCWCag02MMpFyAtC2FikTZTITddocMZmJouoBH4oCX3v3Ak96EvDlL69/\nLtXmcIUUdWUixeYoUiZSyURRABNQJMjW2dMGPUDcVGYCKDcNeSyZAOKIa6jNAaxVJlznv0kmbDYH\nwUcmbGRFJ81NZia4mqOdYDKB8jaHfiDXoUzomYlQmyNk0K3b5ohtp12VMrG8DPzmbwLf/S5w003r\nny9jc7iqOejiVpXNYaKox4S+XJ8yoZOJEJuDENpnwmVzlFUm6rI5gHgykVuZ6HTWKxOxNodt+fpx\nXpZMlMlMcJ+JdoLJBMoHMPUDOUdpqA9mZiLU5ghZ30a1OV7zGuBrX+vNJRG77pTMBCHG5igKYPps\njqIeE/pyXQFMII5M6AG9pkpDgXI2R8pdbwyZiM1MFJEJukjrk7QBbmXCNdGX7XuYmMhTGmpbnw/c\nZ6I/wGQC1SgTRYNJjLypgy5cVSoTg1jNYfbzJ3zmM8A73gG8/e3AmWfWTyZClAna7lBlwkYmispC\n9eXaApjUryFVmchBJja6zaFfzKvITJgXaHP5pjJRppojJTNBNzucmWgnmEygOWUi5QJdVBpaJoBp\nI0JStqOaI0dmwhzgb7kFePGLgV//deDKK9XFz0YmQmyOmA6Y+rJCMhM5bI4YMmGzOcbGeiWtVZIJ\nV2aiXwKYQHU2R4gyUZSZKGNz6GQmRwAzxuYYGelVzHGfiXZiQ5CJKqs56g5ghpaGpgQwbX0maDmD\naHO8/OXA6acDH/pQr+NoqjLR6ayfIM0XwNS3ywWbzSFE73tyLdemTNx1l7/HhL4+WwAT6DWuCpl0\nDfDbHK4pyPu9NBQIJxNSrm9d70OMMhFic/gm+rIpRE1mJswbNlYm2ocNQSaqrOZILQ1NzSEUlYbS\nhaZMO219IHTJzjnQdADztttU8JK6JJYhE8D6z+ILYALq+3BNnU3PA2ttDt+Frcjm8KkSgF2Z0NWF\nmZnmbI5BVCZiiXqKMpFaGlqkTOTITITaHCZZYGWindiQZMJsjZwzMxGqTOzfD2zbFr++otJQmvK6\njDJhIxNN2xy5yYSUwNzc2u9getp+Bxtic9A26ijKTISSO93m8A2a4+Pq+3fZHEVkwvz+9cwE0FMm\n5ufDJnkiMjE0tF5NyZmZKDou2pqZoM9TJjNhszltZKJt1RwpNgeBlYl2YkOSiYmJtXeEOTMTocrE\nvn1pZKKoNJQes2UmUgKYRdNvl0GMvZQ7M3H0qNpHJpkoo0zEkomi78Nmc/gGTSHUslOVCSF6+6nT\nUb9dZCLkQmL69Trqzky00eaoWpkYHV3fDjtWmfBVc9TZTttnc6Raxoy82DBkgloA2y5KVSgTIWRi\n+/b49RWVhuqv0RFywtlsDhqEbZOOlUWTysTcnPodSiZ8RMYmIUtZXpmItTkA+8yhIT0mCNTcy7yz\nBeLJhB7etK3HNgW5LzNRhkzo1mAM6lAmqspM6N/d0JB6LR2jy8trp3p3ZSbaokz4bI6U74iRHxuC\nTCwv99oXV0EmbMqEbzBZXFQX6RQyUVQaSo+lKBO2AGYdZMI1y6WOJsmEHlSzwXbXR4HMMspErM1B\nyzZtjkceUY+FkAkqofWRiZDpx4GeMuEiEy6bw2aLuM7RUDIBpFkdbbI5QpUJIoOmcqBXHdGxGmtz\nLCyo87XOdtrmGMvKRDuxIcgEoJQAwE0myszNoQ82lLb3nSi2C1koikpDAbuEmKpM0MVVD9PlAl0E\nQgbeOsjEpk35bA5fxQM9FqpMhNocgF2ZCCkLJZjKhP6968pEiOWUQiZcweQyykSZacj7TZmg/XTs\n2PpzVlcWQsmEaXPQjYyLKIeirDLBTavaByYTyDs3B+BukGRuSw6bw3ZxsbH+1HbaVSoTrioIG3Jn\nJohM6N9Bqs1hIxO+iodYmyNGmShLJujYNUsLgfw2h0uZcJGJsspESm6iHzMTgLJ2TWVCn1vDRiY6\nnZ5K6LI5FhbCq3l8iM1MmFYyt9NuH5hMIG8AEyieVMp2IQtFUWko4LY5Qttp12lzAGGqUG5lYt8+\ntTx9wCUyYdouoTaHnpQPIROx5C7V5rj77uIeE/o668pMuMiEbV+Pjam74ZTurG23OXJnJgA7mShS\nJvTlukpDFxfzkIkyygS3024nmEwgbwATCFcmqigNpcdsNkeKMlGHzRGy73OQCZpWGeiVhepVPdPT\n6jXm9qTYHDmUCTMzUcbmCFElaJ1FmYlQMjE0pF6XS5kA0hS3JmwOW7jURGpmQsp0MuHLTOjbZFNN\nTGWirnbatlza6mqvSRwrE+3AhiAT09PtUib27VMqwJYt8esLKQ112RwpE30dPaqWV8XJWjeZAHqD\nvNljAugRJtPqqMrmKLoIUqlmrM1hUybOPNP/PkJRAHNpSV2oQu9Kp6byZCZ8beL7VZmItTkmJtQF\nlEp3AT+ZMG8AbDaHPtEX0DsXbUSH3k/HRpPKBNDbx6xMtAMbgkyccIJKtAP5A5guZaLI5ti2Td25\nxWJsTK2TTsRQmyNGmTBtjiosDiCOTBRZDUUwVRcfmTC99ZRqDl8AM1SZoO3WbY6i99j6TNx5J/Do\nRxevi9bnC2ACwN694ReS6em4PhMxygTdofdrZiLW5qB9Pj9fTCYOHEizOUxlwlYa2obMhL6NrEy0\nAxuGTJAyYUuik3UQUqJowqVMFNkcKRYH0Dv56e7ZpUyUmTXUVCaqIhOhAUyqiS8bwKRlAeHKBN0J\nVmFzhFxEdGIYcgdm2hyrq2pejnPOKV4XrU8PYOrbT2Ti4YfDv4vpab8yYZ5zvswEPU8IvbMfH1ef\nq23KREoHTEARVV8HTKDY5jCb0YWQCcpsNJ2ZMM9lVibagQ1BJmZni20OKcN8ThOpykRK+BLonfQ0\n2NvUDZcykRLAtJWY5UKoMmHeRaUglUyYcrANsWQitDSUXlPG5njgAbV/Q8mErkyMja1dX6oy4SIT\nwPrJ0WKUiZg7+9SW2m2yOUxlYmRk/dwuPpsjRplYWlLjgT6+5FQmyvaZAFiZaBs2BJnQlQkXmQDS\nchO2i3RIALMsmaB2ubaJomwSYkzTqrqUidBqjrrIBH1OnUyEtBOvKoBJ213G5rjzTvU7hkxQZsK8\nsyUysbycJzNBy9Lh6zMBFM9s6UJqS+022Ry6MuE6FvTeLbGlofo22ca1tikTMYodo3owmUA5MmEb\nbEICmKk2h65MuE4gG+sPUSaEUHcidZOJov2eY34QG5kwCZ1PmfCtmyZXa6PNQWQitJpDD2C6yAQQ\nfiE591z7um3EFXCTXlsAM5ZMtE2ZSKnmAHrKhI9MAOWrOczlj48rJYm6Cdc5N4dvMkVWJtqBDcHn\nQgKYQD4yUaRMlLE59MyE6wQaHV3b80DKMGUCWF/WduxY82QixGoogk4mlpbUhSXE5vAFKXXoEjK9\nj0iGiRhloqzNceedwKmnhu87IsI2eyuFTHzoQ+71AHYyYSNuZZWJOm2O4eHqlQkXmdAfKxPAtI0X\ntH6aODGHMiGlXV3V0emsHYNsnWFZmWgeG0aZOHBAneA+MpFS0ZFaGpojM+EjE/qgS/0VYmV1QCkT\ng5aZcLUzT1Um6HlTmTBnpyUMD6vvIpTc6UGzFJsj1OIA/MrE5GRPUShzIQH8ZKItyoSUaXe9dWUm\nipSJkNLQWGUCUGPp6Oj6+VNiQOsLyakVzX/EykQ7sCHIxOysGhgOHHC30wbyKhMuMuG6Kw5Fis0R\nM2iZd1VtqOaoi0yMjqqfVDJhdsD0XXAnJ6tTJhYWesHGWDKhBzBNMiFET50ooxLReoD4zEQZMhGb\nmaB9WKXNYZvUzIUQZSLG5qA+Jvr7ijITQFyfERdi1GBXnwlWJtqFDUEmqI3wvn31BDB9g0mZVtpA\nuM1hG3RDlYm6+0wUKUK5MxO+idamp9dedFJtjhAyEZuZCCUTQG+7U8iES5kAemQilzIR2h7bdo5W\nrUzQOVwlmYi5o86RmdCVifHxnnIWYnPoykTZ799mW7ng6zNBnTBZmWgeG4LPVUkmYpWJMpN8AeHK\nREo9PrB+IBzEzEQRmchlc/gG3ImJeNsp1OYAelbHww+n2xw2eys3mYjNTNRZGlo1mQhpuKWD9nmo\nMlFkc+j7OdbmKBO+tK3PB1+fidTviJEfG+IrIDLxyCP21sh1KhNl5uUA1peG2uBSJkJtDlOZqCoz\nEXp3UoXNIYR94isXmUhRJnzvOeMM4LTTirc7VZk4flwRCSBemZifV+s68cT1z9dBJqpSJmJtjjqU\niRgyQceT3mfCRKwyYb4vxObIoUy42qPb4Osz4ZujiFEvNgSZmJlR3uR996n/cwYwY5WJnDaHa5Az\nA5i+eTxM2AKYVSkTw8PqpwkyMTtr96pNMhFqsZhk4tvfBs47z/36f/7nsItUKpmYn4/vMUHrq9Pm\nqDMz0TZlItbmGBpSnzVXZkI/pk1i77M5ms5M6MdOzNjGqBYbIjMxPAxs3eomE2UCmLFNq8pM8gWE\nVXOYAcxYZUKX1ZeWqiMTQK+VuQ+5MxO+appNm9JsDl1CvuceRSae9zz368fHw4J3ZWyOO+9U23Xy\nycXr0dfnCmAC1QcwizpgDlJmItbmANR+92Um9G0talqlf4d1KxO5MhNsc7QHG4JMAMCOHcXKoqIN\nmgAAIABJREFURB1Nq/btU8QmZZIvILw01FbNERvArHL6cUJIJ7wqMhMumymHzfHZz6rP9axnpW8v\noYzNQeHLojp+HXUHMEMzE2VLQzdt6nWODEXbbA5A7XefMqH3Nilqp63v5+Fh9d6QzEROZSLE5vBV\nc7Ay0R5sGDKxfXt9ZKLI5ki1OICwAKZpc8QMuvpASB5zlcqE2TnShipsjlAykWJzfPrTwNOfvrbJ\nUyrK2hwxFgetr8kAZpXttIG43ETbbA6gWJkAeo/bbI6VlV6/Hf2YJhIS0rTqyJF6bQ5fnwlWJtoD\nJhOoP4BZhkzQADA/7x5MxsfV8zQjY0xpqG5z1EUmQpQJylekQu/nH6tMhKybyMT99wPXXuu3OGK3\nu4zNEUsm9A6YTSkTVWUmgDirox+VCaC3TJvNAajj1FQm6H0hyoRt2bGItTlYmWg/mEwgnUxQh7xY\nZSK1kgPoyZGAe5C74ALg0CHg3nvV/7GloabN0QYyUUaVAMrZHCH2CpGJz35Wff/Pfna57SXksDli\n19dGm4MaLJWxOYA4MuGa5rsITWYmADeZ0CekSyET+nlQdwBT/w70G4PU74iRHxuKTNCBF1rNsXu3\nmsLZBbro1qlM6J6oazD5yZ9Uv6+9Vv0ua3NUmZmYmupNHOSCrTdILGLIhNm0KoTIUFL+M58BfvEX\nVbVIDphkIlSZuPNOtT0pygRdrGxkgu7w61YmgPXEM6aDZFttjqqUibGx9dtNx/HCQhiZMLdNX18b\nMhO6zcHKRPPYMGRix47e3+aFaWREDUr6QLW6CrzoRcBHP+pepmuwKWpaVYZMAL1BwDXI7dihZmv8\n5jfV/zFSoN5nog6b48ILge9/3/+aHMqELqvu3x+nTISSiXvvBb72tXwWB7C2MiikbfDIiHoP7dMU\nZcI3K+RFFwGPfnT5PIiNTEjpzkzQtpnKROjFuK02RxWZibEx+3cXo0zYtk2I3tjZZGbCZnOwMtE8\nNgyZ0C/gtrtc867nwAF1UX3wQfcyXRdpX2loWZuDttW2Xh2XX15emajD5njiE4F///devsOGnDbH\n3JwiilXYHA88oEjpr/5quW3VoUv7oTNYTk0BP/iB+vvss+PXd+iQ+tumSF12GbBnT/nvwzYFOU1I\n5yMTpjLRz2QixeYIVSZsZKJsZgLovaeK0tCFBeDP/mz9jVhIB0xWJprHhiQTthPBJBPUqfKhh9zL\ndA02rtLQpSV111dWmQglE//2b+rCGKtM1GlzPPGJ6uJ1zz3u1+QkE/R9FvWZIHITY3MAwM//fHmy\nqCPW5gDU8X3rraq/RGxQbmSkdx6UDdkVrQdYe9Gl9br2t9k/Ze9eVWYdgpTMRBttjlBlwnbOlrU5\naP1ANcrEN78JvP71wHe/23uM5t7Qv4OhIfXDykS7sCHJRIgy8cgj6rePTMQqE2W7XxLoRPSdQJdf\nru70brghXpnQbY6JiXJVFEV4whPUb30AMZEzM0Etpn3KxMpKb5/F2BxAXosDiLc5AEUClpbiLQ5a\nn76cquAjE6HKxG23+buM6qDjuK7MRMjU2ik2RxlloqzNoS8j19wcJjkE1hI+3xjL7bTbBSYTXZj9\nDkLIRKwy4ZtgKgZ0QvtOoAsvVL72tdfGzxqqKxNVWhwAcMopKuPhIxM5lYkQMgH0rI5Qm2NyUt0t\n/dqvldtOE6k2B5BGJnwdFHPCRiaop4cvgKmfV7ffHk4mhIjvglmWTPisO6BaZaIqm6NKZYLOTf07\ncpEFGqdYmWgPNgyZoADm8LB7gpxYm6OINZsoO2MoIUSZGB5W/va116YHMKucMZQghLI6qiYT1HE0\nlkyE2hwveAHwiU8AJ51UbjtN6MdSSJ8JoDfQl1UmqrS36Ng1J5UDevkGE/q+WF1V2Y3HPCZ8nbEz\nh5YhE0CxOlEmM+GzvIqUiTI2R67MBKmdNjKhV3exMtE/2DBkYnpanQiuu0xzjghSJg4e7N0xmfAp\nEzabIzeZKDqBLr9c+ZCLi+EldKYyUeUFhUAhTBdykAnqU/Dww71jwQabMhGy7jPOAJ7//HLbaINu\ncwy6MkEXEVeliH6xu+8+dV6GKhOAIpC+mwMTZclEUW6iKmVifNx+E5DD5silTJgdN4GezWEjEy71\nl5WJ9mDDkAkh1EXcRSZcmQmgx5hNxJaGzs2pi3rqJF+EotJQwuWXq3XefHP4oGUGMKtWJgCVm7j7\nbkXcbMiRmQB6ZMJnMxGZoLvkUJujKtCgubqqZPONTCb08+r229XvGDKxcydw/fXhr6+DTFSRmXjj\nG4HXvW7946bNYeu3U1c1B61PHydjlQmu5mgXNgyZAOLIxL59vYu+624mNoC5b5+6kKVO8qVvq229\nJi67TJGof/3XcDJhdsCsg0w88Ynqt0udyKFMAOqzHT4cRiZibY6qQBfQGKsql82R44LhQlll4vbb\nFfE966zwdT7lKcBNN60t/fWhajJRVQfMyy5TxMlE2Q6Y+jJyEE2XMhGSmTDPC1YmmgeTiS5sysRF\nF6m/XWQiJYCZo2wwlExs2QI87nGqgVEoc687gAkA55+vBilXbiInmQDiyETTyoTpDYcqE+PjKtwa\nC1r+6Gi1d3tEqPULLl1EQjITt92myFLMNl52mVJ4brgh7PVttDlClAkX9MyEjSQXTfQF5LM5gPXV\nOTHKBI1TrEy0BxuKTOzY4ScTZjXHBReoQS9VmTDT3Dm6X9K2AmGD3OWXr31PEUybo47MxMgI8PjH\n16NMAP7vIDUzURXMQTPkO5+ZURfaFAWMjuWqv3fKsJjKxPCw+0KlX3xiKjkIj3uc+lzf+lbY61PJ\nhK0hlw1VdcB0YWhIvacNTavM9UnpJxMuK5mVifZgQ5GJnTvVRcsGM4C5b59q+nPiiWnKBLA+zZ2L\nTISUhhKITMQoE3qfiTqUCUDlJlzKRM7MBDD4NserXw185CNp66N9VGVeQl+XSSY2b+5NZGdC99hT\nyMTwMPDkJwPXXRf2+jbaHJOT6vycn0+7gI6Pq0ncVlaaLQ2l9dH3eeyY+kxAuDLB1RztwoYiE696\nlZq8ywabzbF9uyIUKcqE/jwht81RhTJhttOui0w88YmqBbStV3+dNsfYmPr++tnmOPtsddFMQZNk\n4sgR/5wf+r644464slDCU56ilImiHhBAO20OOhaPHk27gI6P9y7WKTZHVcoEqRI7dqwlE77MhN5n\nosrGeowwbCgy4YN+YBNL3rHDTyaKlAlzMMltc4QMJueeq9YZOvCYE33VYXMAikwsLak20CbqJBPA\n2vk5mlYm6m7OQ8dJU8qEKy8B9M7Re+5R74tVJgBFJh58UJWWFoG2LfZCVXU1B6EqMkENt6pWJnTb\nisjEeefFd8AcGXGrWYz6wGSiC51MUD+IIjIRq0zktjlCLixCqCnJU5SJOm2Oiy9Wv225iSbJRNOZ\nCTqWKM9TtZzbBpvDBbqApJSFEi67TP0OyU2kXqjqUCaAtGNhYqI3kZuLTPgstdzVHLQuquQ499zw\nPhNEstniaAcaJRNCiIuEEN8WQswJId4W+J7/LIR4QAixJIS4RgiRpeegHsCkHhNFNoevz4T+PKAO\n+qKyxJht1ddThNe9DnjDG8Jeqwcw67Q5Nm9WoUFbbqLOzASwnkw0bXMAyucG6lMm6grexpAJutjd\ndpv6+/TT49d58snAmWeG5SZCm4SZqDozQahKmfDNkZI7M6ErE0NDqtQ3tgMmhy/bgcbIhBBiDMDn\nAVwP4FIAFwohrih4z08BeBOA3wJwFtT2/2WO7SlSJmwea5HNoSsTuSb5om0FwgeTJz8ZeM5zwl5L\nAUy6Q6mLTADuttpNKBPUtKoNNgdtBzBYyoROXIHwzMTtt6s72FSf/LLL4pSJWISQidVV9XzdykQI\nmShSJsbGyvfK0dcHKDKxYwcwOxuemaBgMisT7UCTysQzAWwG8Eop5V0AXgvgpQXvOQ/A70opr5FS\nPgDg7wA8KcfG6NUcujJxyilqINcPcEKRzaEPJrlaaQNxAcxY0N1iHdOPmyAyYRK3OktDgXbaHJR0\nr/ourGmbw5eZII89pZJDx1OeAnznO/ZeMDqqJBMx1Tk6yioTZW2OzZvLd/Al6JmJvf9/e+cea2lV\nnvHfOzMc5uLMyIDDMAPiIEesNl5GaqGkUk2IBYM0Ef8YNMVoLcZG0dJiqrESvLQ2JmqFaqyJVquY\nilbGaIVUbYqpBOoYoUCRWwGBgZG5cJsLM+ftH2sv9ne+s+/7299a+zvPLzk55+zrOvt8l+d7nne9\n69Gwrs2aNe3ZJtC/z8SgK+mKyZNSTLwMuMHd9wO4+83AS3o9wd2/4u7bCjedAtxZxWCKKnnnznBF\nvnx5cCagc9QxijNRRcwxzNTQYYlXi1FM1O1M7No1vzhubi58jilqJg4dCge1xRhz5FgzETP2YZYe\n78Rpp4ULhJtv7v24OsREjs5Er5jjHe+AH/5w+PftRLFm4pFHwjT8KCZjEWa/PhO9FjwT9ZJSTKwB\n7i3ddsjMBtK9ZrYOuAj4fBWDKccccZXRXmJimALMaXImDh9uX5nXLSZgfhFmrGOpqmZi2bLeV78Q\n/uannmq/92KMOXKsmYhTdu+7b7RpoZFXvjK8Vr+oY5JiotcJuxd11Ez0cibWroUtW4Z/304Uj7lF\nZwLaY+zXZ0LORD6kFBOHgAOl2w4Ag14TXQn81N2vq2IwZWcinvTHcSbKMceSJfDc51YzVpjMiaUc\nc9QpJo4/Ppzob7+9fVuVJ/Rly4Ir0a86PzoTOYiJumOOlM7EE0/0nxp6//3BrRrHmVi+PAjXfkWY\ndYiJUTpgRsaNObot9DVqBDMs5amh69cvFBP9+kzImciHlJpuF/DS0m2rgQ5ti+bTKtQ8kxCV9OX9\n738/a0tB39atW9m6deuzv5dnc0RnYvXqcDXQzZkwW1gI1smZeOwxWLeumsKlYaaGDkvsM5GiZsIs\nCIoHH2zfNgkx0Y+ymFhMMUfdNRMxG5+bG6wAMzKOmIBQhHnttb0fk2PMUYUzEbelTs7E4cNtF2zY\nsQ1LuQCz6EyUY45eBZhyJqrhqquu4qpSV8e9UXkOQMp/w03AO+MvZrYZmCGIjK6Y2anAZ4Fz3f03\ng7zRpz/9abb08eaKBZi/+U2oFg/v1316aLeDTbcCzCoiDqjHmUgRcwBs2jS/ZiKlmIgH1cUYc9Tt\nTETx2q9mAsLYNm4c771POw2uuKJ3V9ocY44qaiY6/VwcS9z3J72txZqJgwdhz54gJqIzVY45uvWZ\nkDNRHeULbIDt27fzqk5L0HYgZczxn8DqwnTQDwL/7u5uZqvNbMFubGbPI0wn/Ttgu5mtMrNKrp27\nxRwQxMTDDy98TrdpSZ0KMKONV9VYoXkFmBDERNGZiCfRKtyBdetCj4F+KOaoX0zEK9FBnInZ2fE7\nHsbmVTfe2P0xOYqJpUvbn8OoMUckBzFx8GC7YVWnmKNbu2w5E/mRTEy4+2GCM3Glme0EzgUubd19\nM2HqaJmtwLHAR4HHgSda38emLCZizAHVOBMPPzzaktDdxgqTLcCMYqKOk0qRspio8oT+xS/ClVf2\nf1zsM7GYY466CzDjyaPf1FAYP+IAeOELw3vdckv3x+RYMwHt7XFSzkTc9ycdc8SaidhKu5MzEZ2H\nsnjUbI78SNoB092/B5wE/DHwW+5+R+v2zaUpoPHxf+/uSwtfS9y9kiVeZmba85Z37x5MTAzjTFQp\nJiY5NbRYgLlyZTU1HsNw/PHhs5qbC79XKSbWru195RvJMeaIzkQdRXFQvzMRTx6DxBxViAmzIFw7\nOY6RHGsmoF03Ma6YKD8/tTNx7LHBgVi1an7NRLdjrPpM5EXytTnc/VF3/zd3351yHHFHigeXcswx\nijMxKTExSWcixhx1ttIusmlTeP94gEkRNaxaFdyZeEDLwZmoK+Z47nPDVfspp0z2fWB4MRE/i3Gm\nhRbZuBEeeqj7/eOKiVhc2olRYw4YT0zEbfnIIxde7aeqmSiuGArBnSjGHN2OsXIm8kKarkXckWLx\nX9mZ2LkzHByK2V23g035ymTfvjAdq2oxMSlnIsYcqcQEhKhjw4ZqayYGJVr8sdHYYqqZWLkS7rpr\nsu8RGbZmokpnAoKYuO++7vePetU7DTFHp226LCbqms3x6KNBxMYxrVkzX0x0cyZUM5EXyZ2JXIgb\ncrxSKTsTc3PtNtuRbht62ZmIbkfVMcckp4Y+8US900IjRTEBaZyJKKJ27ar/vcvUHXPUybA1E6tX\nh6vpqpyJ446brDORc8zRS0zEmom6+kzEaaGRopjo5jyoz0R+SEy0iDtSPImVnQlYGHUMWoBZtZiY\ntDMBYWdO4UysXx/GkFJMRBEVxcRiijnqpCwmli/vvU2fcw787Gfz981xiDFHp0X8YHQxEd3LSczm\ngPb2OMrYhnEm6qqZKM90G8SZ0GyO/JCYaBF3pIceChtnscdVNzExaAFm1WJidhbOOCMs11s1cex7\n96YRE0uWhM8pBzGRW8xhVn9B7CQpxxz9imNnZtpTOqtg48Z2BNmJUcVEbGQ3qZijqpqJMilijmee\nabfSjqxePXgBppyJfGjQoWk8is7EMcfML06KG/o4zsSRR4bldatg/Xr46U+re70i8apqz540MQfM\nb1yVsmYit5ijaQfNsjMxyEybKonivtuMjlHFBCxsFV5mnJhj0jUTdcUcRWeiW8zRrwBTzkQ+SEy0\nKIqJso0ahcA4zsSGDeM32qmD1M4EzO81ceBA+NzqPGAUnYkjjkjrBhSdiaYdNItX7/2WH58EsYtm\nt7qJSYqJVLM5Bo05liyZ/HYf6x527Ogec3RzHmIBppyJfJCYaNFLTEDn6aHdDjbR5iyKiaoijkmT\ng5gors9x4EDnaWyTpCgmUroSMF9MNO2gmYszkVJM1D2bIz63k9NXFBN1bGvx/coxx6A1E+ozkRcS\nEy3iSSPGHGU6iYluGzrMP5hMk5goxhy5OBN1n9CLMUdOYqJpB81hayaqZuXKMCVxEjHHIDUTS5Ys\nbBM9CHXM5ph0vUTx/WChmOhXM6E+E/khMdEibthPPz2+MwHtjR3C86ZFTBRnc6SsmXj88XBQ27+/\n/tkUMzPhc3jssbQzOaBtNTddTKSIOaD39NBJ10yMesKO2+QoQmTQmKNOZwLmxxyxaZV7d+eh2AFT\nYiIPJCZaFDfsqsTENDsTc3NpnQkI7kQKZwLC3757d3pnwixsS02NOWKXyBQxB/TugjnpmGNUMbFi\nRef1KgZh0NkcdWxrxfcoOxPPPBP2/V59JqCZIntakZhoUdyxq4o5og23c2d7emnuFHfMxSwmYkvt\n1GIC2mKiaQfN1DUTkFZMjHrC7tePoxe9nIn4milijnIBJoRtol9jwCaK7GlFYqLFIM7E3r3t5kEw\nmDPxyCPBrpsWZ0JiIhAjntQxB4T/SdPFRIqaCQj7ZaqpoeM6E6PQS0wsXRq+6o45VqyYf6yJ28ET\nT/SfMdfE/WJa0b+hRXHn6uZMQBAHsVnUM890P9lEZ6LqhlWTppjDpqqZWLEiTMX99a9DzURKMZGL\nMzE317wrsBxqJopdMMuxQa4xx9atcMIJoz23V8wBYUxPPVWPkxr//mOPnf/ZF5ch79VnAuRM5ITE\nRItBnAkIUUcUE4MUYE6bmMjBmYD2jI4DB9K4A7mJCWjeFVixiG7//nQxx/79YfZSuQlcrjHH5s3h\naxR6ORMQjoP79tUTc8S/vxhxwPyY49Chzvu/nIn8UMzRorhjdxITscFN7MwIg00NffjhUJFf3mFy\nJRcxEXtNKOZo/0+adtCM+8ggK4ZOirhfd4o6xpl2OMmYYxwGERNQb8xRLL6E4WomNJsjHyQmWsSq\neYCjj154/9FHh428uDzzoM7E+vWjTeNKQQ4xB8x3JhRzzP/eFOIJNzYoSlUzAZ2LMHONOcZhkJgD\n8hATvWomirc1TWRPKxITBWZmQhObThuvWVhgqygmBnUmpiXigHyciSgmUtdM5OBMND3mGGT58Umx\n2MTEoM5EyphjxYrg5vaqmSje1jSRPa1ITBSYmem9vPHJJ8Odd7Z/H9SZmCYxUXQmUouJHTtCE7EU\nJ/T4t+fgTDQ95kjpTMRi3xRiIsVJcBpiDrN2S+1+fSagefvFtCIxUeDIIzvP5IjMzs4XE72ciTg1\ndNrERE7OxNwc3H+/Yo6mxxwpayag+/TQXKeGjsOSJWFsOYmJTvVkUUwMEnM0bb+YViQmCvRzJmZn\nw0EnLtHb62BTnBo6jWLCrL0GQApir4nUYkIxx+TIwZmA7o2rmhhzAHzsY/CGN3S+r86YY8MG+NSn\n4OyzF94X1+fo12ei/LNIh8REgUHEBLTrJvrFHAcPTte6HNCOOVatSrtkehQTc3NyJpoac8TFsKKY\nSFXwOykxEdfm6USqmAPgAx+AU07pfF+dzoQZXHIJrF278L64Pke/PhPln0U6JCYKvP718LrXdb+/\nLCb6FWDu2BEOSNMkJuKOmzLigBA3xQOb+kzM/94Uis7E6tXtRc3qZhJi4sQT4aabursTqWKOftQp\nJnrRr2ZCzkR+SEwUuOIKuOCC7vcffXSY7RHrJvo5Ew88EH6eJjERnYnUYsKs7U4o5gjfm3bQjH/P\nnj3pIg5o10y4z799HDHxrneFiO573+t8f8qYoxd1xhy9UM3E9CExMQRm82d09HMmYoOraRIT8eCZ\nssdEJAcxkYMzEf8nTTtoxr9r1660YmLjxtDPZPfu+bePIya2bIHTTw8XKJ3IXUyk3taGERNNE9nT\nisTEkBRndAy6BPm0rBgK+cQcIDERabozsXt3mh4TkdgFsxx1jCMmAN7zHvjxj+HWWxfel7Jmohe5\niInVq9sFmOozMR1ITAxJUUz0mxoKsG5dHiekQckl5oC2mEhZM6GYY3IUxUTqmAPmTw+dmwtf43zm\nb3pTuJC48sqF9+VeM5F6bOozMX1ITAzJ7GxYOTRu6L2mhsJ0RRygmCOSY9Oqpl2B5RJzdOqCefhw\n+D7OiWpmBi66CL76Vdi7d/59ijl60y/mkDORHxITQxJndNx992DOxLSKiZycCcUc4XvTrsCKYiJl\nzLF8eXAQi2IiRpTjfuYXXRTqMb785fm3K+boTewz0e1zUgFmfkhMDEkUE3fe2UxnIseYQ2IifG+y\nmEjpTMDC6aFViYnjjoPzzw9Rx9xc+/bcY47UJ+goLgfpM9G0/WJakZgYknXrQi//X/2qd6Y6rc5E\nnOufg5g4/vjwPUUnzk2b4PLL4bWvrf+9yzQ95kg9NRQWttSuSkxAKMS86y7Ytq19W+4xR+qxFbcH\nxRzTgcTECMzOwu23h597TQ2F6RMTZsGdyKFm4sQT4StfgbPOqv+9zeDDHw7CMTVNdybm5tKLibIz\nEbtXVvGZn346nHlmcCje974gnhRz9KafmCguSNi0/WJakZgYgdlZuO228HPTnAkIY8/BmTCDCy+E\nlStTjyQtTRcTkLZmAiYXc0DYjq+7Dj7xCfjSl+BFLwoFmamv/jsxLWLCrLmdYacViYkRmJ2FO+4I\nPzetABNC9XmvTqCiXpoec0B6Z6LcBbNKMQHhJH3ppeG4cdZZwflYt66a166SXGKOorjsV5fWNJE9\nrUhMjMDsLOzbF35uWgEmwJvfPF2NtprOYnAmUouJjRtD9LBrV/i9ajER2bQJvv51uOceeOtbq33t\nKpgWZ6J4e+qxioDExAjEGR3QTGdC5IXExOQpd8GclJiIbN6c/uq/E7mIiaIz0a8urWn7xbQiMTEC\nJ5/c/rnbhrxqVVgULIfaAzHdNDXmKBbR5VAzAfCd74SoY9JiIldyiTlmZtrdZ+VMTAcSEyNw1FFh\nBVHoviG//e3wox/VNybRXORMTJ7nPx8uvhguuwzOPjus+AnN+8z7kYszAW2B2a/IfbH9j3JFYmJE\nYtTRbUNeuzasHCjEuDT1oJmTmDCDz3wGfvAD+OUv4bzzwu1N+8z7kZOYiNtEv5gjh7EKiYmR6Scm\nhKiKph40cxITkbPPhltugXPPDQ3cogO5WMgl5oD+YqKpInta0b9hRKKYaNoBXuRHUw+axQK6HNqW\nR445Br71Ldi5E9avTz2aepkmZ0I1E3khZ2JE5EyIumi6mFizJsQMOWG2+IQE5CUm+tVMaDZHXkhM\njMipp4bZGpr6KSZNU6/AimJC5ME0xhxN2y+mFWm6ETn5ZNi9O/UoxGKgqVdgEhP5kZMzMUgBpll7\ncUKRFv0bhMicpl6BRTGRuseEaDNNYuKII/IYpwhITAiROYuhZkLkwaZNoVlUDu30B+kz0bR9YprR\nv0KIzFHMIepi82Z48sn53UlTMUjMIWciH+RMCJE5ijlEneQgJGCwmKNpAnuakZgQInOaGnPEwjk5\nE6ITp50Gb3xjd7EpZyIvGnZ4EqJ5NDXmMAt/k8SE6MSLXwzXXNP9fhVg5oWcCSEyp6kxB4Riv6OO\nSj0KMY0o5siLpGLCzH7bzG40s8fM7JMDPudMM7vNzB41s/dNeoyLlauuuir1EKaOSX1mTY05AL7/\nfVi5UtvasGj/HC3m0Oc2OZKJCTObAbYBNwGnAi8xswv7POcY4Brg68DpwFvN7MxJj3Uxop1ueCb1\nmZ10ErziFWGZ7KbxmtfAtm3a1oZF++dozoQ+t8mR0pk4B1gDXOLu9wIfAv6kz3PeAjzo7h9397uB\nywd4jhBTzYYN8ItfLL4VLIXohWom8iKlcfoy4AZ33w/g7jeb2Uv6POflwE8Kv98I/O2ExieEECJT\nzjsPXtLvjCFqI6WYWAPcW7rtkJmtdfe9PZ5za+H3x4GNkxicEEKIfDnnnNQjEEVSiolDHW47AKwE\nuomJQ63HRPYDK3q8x3KA22+/fZTxLWr27t3L9u3bUw9jqtBnNhr63IZHn9lo6HMbjsK5c3m/x5q7\nT3Y03d7Y7FLgpe5+YeG23cDJ7v5Yl+f8A7DT3T/S+n0t8Gt379jWxMwuIBRrCiGEEGLdJSMYAAAG\nNElEQVQ03uLu3+j1gJTOxE3AO+MvZrYZmAF29XnOBYXftwAP9nj8tYSizf8juBhCCCGEGIzlwAsI\n59KepHQmlhKEwAfc/Z/M7B+B9e5+npmtBva5+6HSc44G7gfOBa4nTBO9090vrnn4QgghhGiRTEwA\nmNm5wFXAPuAwcKa732Fm9wIXu/u2Ds/5U+BzwJPAbuB0d99Z47CFEEIIUSCpmAAws/XAqwjTRHcP\n+JwTgRcD17v70x3uP8HdH6h2pEL0xszOAH4lcSuEWGwkFxNVY2ZHEOouznT37aX7TgDOBJ7j7l9I\nMb5pwMyuJsRHf5V6LLliZjPufrB0293A59z9M/0eK4QQTaKB3f55LXCXu283sx8Aq4DnAScAO4Ht\nwG1mZt40JVUdzwA6+XXBzI4Hfm5mTwPlbei9Zvbewu9LCVOdX1bX+IQQom6a6Ex8E/hfd7/MzA4A\nJxFqKz4C3O/uVyYdYGaY2XnAZ2ifFA04hiAo9hRuAzjL3e+qd4RCCCFyp1HOhJk9H/gj4IOtm+bc\n/cHWff0aXC1WjgR2u/uWeIOZfY0Qc1xeuG0uxeByx8wOA3cQCoiLHAV8390vqn9UQghRL40SE8CH\nCVfUnXiSEHlgZsuApe5+oMtjFxPDiAQJioXsAz4OPFG6/fUsjECEEKKRNEZMmNnvEVYi/Wbp9nsI\nNv0KYFVrmfNlhCYc7yy/ziJEJ7zx+HPgOa2vIjcD6uMuhFgUNEZMEAorzyN0vHwWdz8JwMx+H/iQ\nu/9hgrHlzDDL0Kdcsj4rzOwLwBn0EWNmZsC/uvtf1zIwIYRIQGPERGsp8/82s7d0ecgthCXMxXzm\ngONaDg4UCjDN7G2F23YiMVHkOOCj7v4vvR5kZpcAm+sZkhBCpKExYqILDmBmF7v7Z83sITPbUu4/\nsZhx928D3y7e1qkAUyzg2foRM/svQswR1385CrjZ3d9UfqwQQjSRpl9pLjGzbwB/YGYzhNbdfwnh\nitHMNiQdnWgKjwPnu/ur3f3VwF/QvRBYCCEaRxOdiSOAZa2W28sIRXBbgDcAnyc0rHoHcClanrwb\nS2m+0ByX4ufzEPDPrfoICI7YfxQepyJXIUSjaaKYOBJY7u73mdnvuvvPzexFwJXANuB8gq1/nbvv\nSDnQjHkOYTl40Z1nPx93f3unB5jZu4G3AR+qaUxCCJGExnXAFCIXzGyZux9KPQ4hhJg0EhNCCCGE\nGAvl4kIIIYQYC4kJIYQQQoyFxIQQQgghxkJiQgghhBBjITEhhMgCM3tvq/04ZrbUzGYKvTuEEBkj\nMSGEqBUzu8zMOq1p8gvg42b2KuACYC+wx8x2tb52m9nBVv8OIURGSEwIISrDzA6b2Z7Cif/POjzs\nYOtrHu5+PaG53Bp3/5q7r3D3te6+rvV1FHAt7TVQhBCZ0MQOmEKIdBwAXunu95rZNuCQmX2EsFbJ\nHKG1+BnAsWb2IeAad/8fM7sLeLe7XzLAe6gRmBCZITEhhKiSw4Ql62l9fwa4lSAADhHExCyhHfmt\nhCgDglNxAMDMbgZWtx4bX+sL7v7JGsYvhBgBiQkhRJXMAdvNzIGVwNXufrWZvdzdfwlgZi8Glrj7\ndwvPO0x7QbRjgVPd/YHW4/8GWFHbXyCEGBrVTAghqmSOEHMcBVwHuJnNAjeY2QuGeI3ysWmushEK\nISpHYkIIUSVLaEcTALj7ncDVwIeHeJ3rzeweM7sXeFeF4xNCTACJCSFElSwt/R6FxReBfUO8zhnu\nfpK7bwa+UMnIhBATQzUTQogqWQrc2KqZWA18F56d9nn9gK9hLLzQ0YWPEBkjMSGEqJJlwO8UpoYe\nMcJr7AB+0mp+aYTCTLkTQmSMxIQQokoeJczMAHgn8HSHx6yhPXMjspLW8cjdX9HphVuttY/p8ppC\niIRITAghKsPdNxV+fqR4n5mtAm4g9Jm4qPTUVcDybq9rZkcDdwIPAz+tarxCiGow9/IFghBCTIZW\nj4lH3X3XCM/d4O47JjAsIcSYSEwIIYQQYixUIS2EEEKIsZCYEEIIIcRYSEwIIYQQYiwkJoQQQggx\nFhITQgghhBgLiQkhhBBCjIXEhBBCCCHGQmJCCCGEEGMhMSGEEEKIsZCYEEIIIcRY/D8jzm+zuHAm\nQwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc449320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 除了通过plt对象外，我们还可以通过子绘图对象来设置与获取标签与刻度\n",
    "figure,ax = plt.subplots(1,1)\n",
    "ax.plot(np.random.random(100))\n",
    "\n",
    "# 获取x轴刻度范围\n",
    "print(ax.get_xlim())\n",
    "\n",
    "# 设置x轴的显示范围\n",
    "print(ax.set_xlim(0,120))\n",
    "\n",
    "# 获取x轴显示的刻度，\n",
    "print(ax.get_xticks()) # 返回的是数组\n",
    "\n",
    "# 设置x轴显示的刻度标签。默认显示的是就是刻度值\n",
    "ax.set_xticklabels(['低','中','高'])\n",
    "\n",
    "# 设置x、y轴的标签说明\n",
    "ax.set_xlabel('时间')\n",
    "ax.set_ylabel('数值大小')\n",
    "\n",
    "# 设置标题\n",
    "ax.set_title('波动值')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "mpl.rcParams[\"font.family\"] = \"SimHei\"\n",
    "mpl.rcParams[\"axes.unicode_minus\"]=False\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 添加注解\n",
    "我们可以在图形上绘制文本等说明信息（注解）。\n",
    "### 普通文本\n",
    "plt.text 显示文本（基于坐标）  \n",
    "plt.figtext 显示文本（基于图片）\n",
    "\n",
    "### 箭头\n",
    "plt.arrow 根据起点坐标（x，y）与各自轴的长度（x + dx, y + dy）绘制箭头。\n",
    "* width 箭头尾部的宽度。\n",
    "* head_width 箭头的宽度。\n",
    "* head_length 箭头的长度。\n",
    "\n",
    "### 箭头与文本\n",
    "plt.annotate 显示箭头与文本。\n",
    "* xy 箭头指向坐标\n",
    "* xytext 文本起点坐标。（箭头尾部坐标）\n",
    "* arrowprops 字典类型，可设置箭头的属性。\n",
    " + facecolor 箭头的颜色\n",
    " + headwidth 箭头的宽度\n",
    " + width 箭尾的宽度\n",
    " + shrink 收缩大小\n",
    " + headlength 箭头的长度\n",
    " + arrowstyle 一些预设的箭头样式。当含有该参数时，上述4项参数将不再有效。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Annotation at 0xed747b8>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TPPlk7CQiIiKbN24czJsXjl+SmVQwpqB994WTToKhQ9XIW0REUpt7OF516ABNmsROIyVF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\nJCwFRhEREREJ6/8BzzFccucoWwgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xece74e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(-10, 10, 100)\n",
    "plt.plot(x, x ** 2, \"-\")\n",
    "plt.title(\"抛物线图\")\n",
    "\n",
    "# 在指定的坐标位置增加文字说明。\n",
    "plt.text(-1.5,5,'这是极值点')\n",
    "plt.ylim(-10,100)\n",
    "\n",
    "# plt.text与plt.figtext都可以进行文字说明，不同的是，text是基于坐标定位，而figtext是基于比例定位（左下角为原点）。\n",
    "plt.figtext(0,0.1,'figtext')\n",
    "\n",
    "# plt.arrow 根据起点坐标（x，y）与各自轴的长度（x + dx, y + dy）绘制箭头\n",
    "#plt.arrow(7, 20, -5.5, -15, width=1, head_width=4, head_length=4, color=\"r\")\n",
    "\n",
    "# 使用text与arrow可以实现箭头与文本的说明。我们可以使用plt.annotate可以将箭头与说明文本一同绘制\n",
    "plt.annotate(\"这是极值点\", xy=(0, 0), xytext=(11, 25), arrowprops=dict(arrowstyle=\"->\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# 图形类型\n",
    "## 折线图\n",
    "plt.plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xedbe5f8>]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sMIhg0NTkGvTyecxzUDZuhI8/zn3EAFyfwU03+VtXlCxatIhFLQ7M2e/DGldf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\n/z8oFEgyHU5eMgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xeafa2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 适合于具有增长趋势的数据表达\n",
    "plt.plot(np.arange(1, 13), np.random.randint(50, 100, 12), \"-o\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Series与DataFrame图形绘制\n",
    "Series与DataFrame类型的对象也支持图形绘制，使用对象的plot方法即可。  \n",
    "如果我们需要绘制图形的数据就存在Series或者DataFrame对象中，我们就可以直接绘制，而无需使用plt.plot。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 其他类型图形\n",
    "plot默认绘制的是线形图，我们可以通过调整其kind参数的值来绘制其他类型的图形。\n",
    "* line：线形图\n",
    "* bar：柱形图\n",
    "* barh：条形图\n",
    "* hist：直方图\n",
    "* kde / density：核密度图\n",
    "* pie：饼图\n",
    "* box：箱线图\n",
    "* area：面积图\n",
    "\n",
    "参数：\n",
    "* color\n",
    "* alpha\n",
    "* stacked：是否堆叠。\n",
    "\n",
    "说明：\n",
    "plot(kind=\"类型\")也可以通过plot.\"类型\"来进行绘制。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     1\n",
      "1     3\n",
      "2     8\n",
      "3    10\n",
      "4    12\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "s = pd.Series([1,3,8,10,12])\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10078ef0>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZEIiIFwEfB9YD+wKLgB9HxC5ZvYdUJFu7Bl7xlivsGigpt7IsDZwC7Aa8IaW0KSJmAHcD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\n6i4BBeDUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x100ab860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot(kind = 'line',marker = 'o',color = 'g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x101741d0>"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZEIiIFwEfB9YD+wKLgB9HxC5ZvYdUJFu7Bl7xlivsGigpt7IsDZwC7Aa8IaW0KSJmAHcD\n7wAunegFixYtore3d5tjAwMDDAwMZDgtafrZNVBSFmq1GrVabZtjmzdvzvQ9IqWUzUARHwGOTikd\nM+bYcuD+lNL/GffcPmD16tWr6evry+T9pbxY/qvlDHxngHOPOJfPHvvZTk9HUskMDg7S398P0J9S\nGpzqeFleI/AgsOu4Y/sCD2X4HlKu2TVQUtFkGQRuAA6OiPdGxCsi4mzqtxBek+F7SLll10BJRZTZ\nV6qU0mPAm4B3AfcC/wicllLyjIBKz66Bkooq0z4CKaWVwBFZjinlnV0DJRVZ5p0FpSqxa6CkojMI\nSC2ya6CkMjAISC0Y2zXwxjNutGugpMIyCEgt2No1sHZKza6BkgrN+5ukJtk1UFKZGASkJiz/1XIW\nfn8h5x5xLgtft7DT05GkKTMISA2ya6CkMjIISA2wa6CksvKrmTQJuwZKKjODgLQDdg2UVHbePiht\nh10DJVWBQUCagF0DJVWFQUAax66BkqrEICCNY9dASVXixYLSGHYNlFQ1BgFplF0DJVWRQUDCroGS\nqssgoMqza6CkKvMrnirNroGSqs4goMqya6AkefugKsqugZJUZxBQ5dg1UJKeZxBQpdg1UJK2ZRBQ\npdg1UJK25cWCqgy7BkrSCxkEVAl2DZSkiRkEVHp2DZSk7TMIqNTsGihJO+ZXRZWWXQMlaXIGAZWS\nXQMlqTHePqjSsWugJDXOIKBSsWugJDXHIKDSsGugJDXPIKDSsGugJDXPiwVVCnYNlKTWGARUeHYN\nlKTWGQRUaHYNlKSpMQiosOwaKElT51dOFZJdAyUpGwYBFY5dAyUpO94+qEKxa6AkZastZwQi4qaI\neGc7xlZ1je0aeNMZN9k1UJIykHkQiIgzgOOzHlfVNrZr4DVvvcaugZKUkUxLAxHxEuBzwG+yHFey\na6AktUfW1wh8HrgG2DXjcVVhdg2UpPbJrDQQEX8PHAV8CIisxlW12TVQktorkzMCEbELcAnwvpTS\nUxGN5YBFixbR29u7zbGBgQEGBgaymJYKzq6BkqquVqtRq9W2ObZ58+ZM3yNSSlMfJOJTwD4ppXeM\nPv4q8K8ppSu28/w+YPXq1avp6+ub8vurfO7ceCdHfu1IjnjlEawYWGHDIEkaNTg4SH9/P0B/Smlw\nquNldY3AALBnRGwafbwbcFpEHJpSWpDRe6gi7BooSdMnqyDw38aN9XlgJfC1jMZXRdg1UJKmVyZB\nIKX0H2MfR8QQ8EhK6bEsxlc12DVQkqZfW1oMp5T+dzvGVXmN7Rr4w3f90K6BkjRN/F0D6rixXQNv\nPONGuwZK0jQyCKjj7BooSZ3jryFWR9k1UJI6yyCgjrFroCR1nkFAHWHXQEnKB4OApt2dG+/k5OUn\nc9Sso7hs3mV0hR+GktQpfgXWtLJroCTli0FA08augZKUP94+qGlh10BJyieDgNrOroGSlF8GAbWV\nXQMlKd8MAmoruwZKUr55saDaxq6BkpR/BgG1hV0DJakYDALKnF0DJak4DALKREoJsGugJBWNFwuq\nZUNDQyz+5GJW3LKC4RnDxHDw6J6PctBJB9k1UJIKwiCglgwNDXH4cYez5oA1jMwbgQASsBae/sbT\npHcl2LnTs5QkTcbztmrJ4k8uroeAA0ZDANT/+1/hvr++j/OWnNfJ6UmSGmQQUEtW3LKCkdkjE/7d\nyOwRrrvlummekSSpFQYBNe3Z555lc9r8/JmA8QKGu4b/8wJCSVJ+GQTUsE1/2sRnf/JZZn9xNps2\nb6pfEzCRBN1buonYXlKQJOWFFwtqUuseW8eyny7j8jsvZ3hkmLe/5u0886ZnWL5++YTlga51Xcw7\ndl4HZipJapZBQBNKKfHj3/6YC1ZdwLW/uZY9dtuDcw4/h7P+7ixe/uKXM3TUEHcddxdr0pp6GBi9\na6BrXRdz1s5hyUVLOr0ESVIDDALaxvCWYb59z7e5YNUF3PEfdzBnzzl8+YQv8/a5b2fX7l3/83k9\nPT2svHkl5y05j+tWXMdw1zDdI93MO2YeSy5aQk9PTwdXIUlqlEFAQL3+/5XBr/DFn32RB594kGP3\nP5abzriJ42Yft93ugD09PSw7fxnLWEZKyWsCJKmADAIVN1H9f+HrFvKal7+mqXEMAZJUTAaBCpqs\n/i9Jqg6DQIU0Wv+XJFWHQaACWqn/S5KqwSBQYlnV/yVJ5WUQKBnr/5KkZhgESsL6vySpFQaBgrP+\nL0maCoNAQVn/lyRlwSBQINb/JUlZMwgUgPV/SVK7GARyzPq/JKndDAI5ZP1fkjRdDAI5Yf1fktQJ\nmQWBiDgJuADYB7gbGEgp3ZvV+GVl/V+S1EmZBIGI2B+4HHgvcBvwJeBS4L9nMX4ZWf+XJOVBVmcE\n5gAfTil9ByAiLgauz2jsUrH+L0nKk0yCQErphnGHDgLuy2LsMrD+L0nKq8wvFoyIbuCDwOeyHrto\nrP9LkvKuHXcNfAJ4ErisDWMXgvV/SVJRZBoEIuIo4P3AYSmlLZM9f9GiRfT29m5zbGBggIGBgSyn\nNW2s/0uSslSr1ajVatsc27x5c6bvESmlbAaKmAWsBD6YUrpqkuf2AatXr15NX19fJu/fKRPV/896\n7VnW/yVJbTE4OEh/fz9Af0ppcKrjZXX74Ezqdwl8F7g2Il4EkFJ6Kovx88j6vySpDLIqDRxH/U6B\ng4D3AAGkiJiVUvptRu+RC9b/JUllktXtg9cBM7IYK6+s/0uSysjfNbAD3v8vSSo7g8AErP9LkqrC\nIDCG9X9JUtUYBLD+L0mqrsoGAev/kiRVMAhY/5ck6XmVCQLW/yVJeqHSB4G1j61l2aplfPUXX7X+\nL0nSOKUMAtb/JUlqTKmCwPCWYb51z7e4YOUFrN642vq/JEmTKEUQ2Fr//8JPv8BDQw9Z/5ckqUGF\nDgLW/yVJmprCBQHr/5IkZacwQcD6vyRJ2ct9ELD+L0lS++Q2CFj/lySp/XIVBKz/S5I0vToaBE44\n/QROnXcqH//ox/ne775n/V+SpGnW0SCw8ciNfGnjl7j40It57tTnOHaO9X9JkqZTx0sD6YDEc+k5\nTh86nSvfcWWnpyNJUqXk48fuA+D222/v9CwkSaqcfASBgOGuYVJKnZ6JJEmVko8gkKB7SzcR0emZ\nSJJUKbkIAl3ruph37LxOT0OSpMrp+MWCXWu7mLN2DksuWtLpqUiSVDkdPSOw1217sWDvBay8eSU9\nPT2dnIokSZXU0TMC1195PX19fZ2cgiRJlZaLawQkSVJnGAQkSaowg4AkSRVmEJAkqcIMApIkVZhB\nQJKkCjMISJJUYQYBSZIqzCAgSVKFGQQkSaowg4AkSRVmEJAkqcIMApIkVZhBoM1qtVqnpzAtXGe5\nuM5ycZ3aEYNAm1XlA9N1lovrLBfXqR3JLAhExKsj4mcR8WhEnJ/VuJIkqX0yCQIRsTNwHfBz4LXA\nwRFxZhZjS5Kk9snqjMCbgN2Bc1JKG4DFwPyMxpYkSW2yU0bjzAVWpZSeAUgp/TIiDt7B82cCrFmz\nJqO3z6/NmzczODjY6Wm0nessF9dZLq6zXMZ875yZxXiRUpr6IBGfA3ZJKf3jmGN/AP46pbR5guef\nDlw55TeWJKm6zkgpXTXVQbI6I/DcBMf+DOwGvCAIAN8HzgDuB57JaA6SJFXBTGA/6t9LpyyrIPAY\n8Kpxx3qAZyd6ckrpUWDKKUaSpIq6PauBsrpY8OfAEVsfRMQsYGfqAUGSJOVUVkHgNqBnzC2DHwVu\nSVlcgCBJktomk4sFASLiRKAG/AnYArwhpfSbTAaXJEltkVkQAIiIlwH91G8l3JTZwJKk7YqIXuBA\n4N9TSo93ej7tVKW1TpdMf9dASumPKaWbgFc02244Io6MiHsi4o8RsTDLebVLK22VI+K6iBgZ/bMl\nIm5u9zyzEBF7RsT6iNinwecXbj+hpXUWbj8j4qSIWBcRwxExGBEHNvCawu1ni+ss4n6eRv0OrK8A\nv4uIUxp4TeH2E1pea+H2dKuIuCki3tnA86a2nymlTP9Qv0hwPXAhMAtYAZw5yWv2BB6n3pFwNnAH\ncGTWc+v0Okdf9xAwh3onxt2BXTu9lgbmvCewknrJZ58Gn1+o/WxlnUXcT2B/4FHgFOClwNXAj8q2\nn62ss6D7uTvwR+BVo4/PBDaUbT9bXWsR93TMvM8ARoB3tns/2zH5k4FHgJmjj+c28IXmA8Cvxzye\nB3y90xvRhnXuDTzU6bm3sNb/ByxoIggUbj9bXGfh9hN4MzB/zOM3AE+WbT9bXGcR9/OvgIExj18D\nbC7bfk5hrYXb09F5vwTYCNzTQBCY8n6249cQv6DdMLCjdsMAfwP865jHP6N+rUGetbLOQ4GdIuJ3\nEfFkRNRG6115Nz+l9CUgGnx+EfcTml9n4fYzpXRDSunSMYcOAu6b5GWF288W11nE/XwwpVQDiIhu\nYBFwzSQvK9x+QstrLdyejvo89bWtauC5U97PdgSB3YEN4449N8k//vjXPEE9yeVZK+s8CPgF8Ebg\nMOolhU+3Z3rZSSk90ORLirifrayzkPu51egX0w8CF0/y1ELu51ZNrLOw+xkRc6n/BHk89Z8Qd6To\n+9nMWgu3pxHx98BRwIdo7IeSKe9nO4LAc9TbC4+1td1wo695Btg143llrel1ppQ+k1I6PqX0q5TS\nr4FzgVPbOMdOKeJ+Nq0E+/kJ4EngskmeV/T9bGidRd7P0TOSx1I/61Hq/WxmrUXb04jYBbgEeF9K\n6akGXzbl/cyqxfBYTbUbHvOalzbx/DxoZZ3j/RHYIyK6U0rDmc2s84q4n1kozH5GxFHA+4HDUkpb\nJnl6YfezyXWOV5j9BEgp3RkR7wLWRcTuKaUntvPUwu7nVk2sdby87+k/AT9LKX2viddMeT/bcUag\nlXbD27wG6KN+pWeeNb3OiFgeEa8fc+gI4A85/YCciiLuZ9OKup+jH6tXAWellO5t4CWF3M9m11nE\n/YyI/xERnx1zaJj6leYjO3hZUfez6bUWcE8HgJMiYlNEbAJOBy6KiC/t4DVT3882XO04A/g9o7fS\nUb/f89rR/+8BdprgNXsAT1Gvi3QDNwLLOnG1ZpvXuZj6hRyvp37XwUbgvE6vpYk1jzDmavoy7WeL\n6yzcflL/rWW/pn768UVb/5RtP1tcZxH38y+p3zo2n/pV9V8Dri/bfk5hrYXaU+q1/X3G/PkW9etb\n/ks797NdizmRek3uYerfLA8cPb4BmLed17yXep3jUWAt8NJOb0rW66ReirmU+sUcD41+kHZ1eh1N\nrHeb2+rKtp/NrrOI+0n91qItY/6MjP533zLtZyvrLOJ+js77aOBXo98krwb2GD1emv1sda1F3dMx\n87+c0dsH27mfmbYYHquVdsMRsS/1qzx/lFJ6ui0Ty1gr66yKIu6nts/9LBf3s1ymsp9tCwKSJCn/\n2nGxoCRJKgiDgCRJFWYQkCSpwgwCkiRVmEFAkqQKMwhIklRhBgFJkirMICBJUoUZBCRJqrD/Dyxc\n6i4BBeDUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x101a7470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot.line(marker = 'o',color = 'g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10375080>"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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e5I6J1gYAlrRvonVuSfK5McZ2kowxHqqqm86x//4kefjhhyd6+P/ve2t+Kcl88uWTp5I8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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1037d6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot(kind = 'bar',color = 'g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xfef6dd8>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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J3pLk5UmuTfKpJH+00KFOkKp6XvbfkskxVdXpJC9K8ouLnmXZHfz9/I0kz0nyxCSfSfLH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\ndEjgAaBD/w/YpHQmXpY5OAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfed1d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot(kind = 'barh',color = 'g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11978a58>"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x120a2320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot(kind = 'area')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11bdfd68>"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a374a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame({\"A\":[10, 5, 8, 7], \"B\":[12, 11, 3, 6]})\n",
    "df.plot(kind = 'area')"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
